When Do Potential Functions Exist in Heterogeneous Routing Games? 1

Size: px
Start display at page:

Download "When Do Potential Functions Exist in Heterogeneous Routing Games? 1"

Transcription

1 Whn Do Potntial Functions Exist in Htrognous Routing Gams? 1 Farhad Farokhi 2, Walid Krichn 3,4, Alxandr M. Bayn 4,5, and Karl H. Johansson 2 Abstract W study a htrognous routing gam in which vhicls might blong to mor than on ty. Th ty dtrmins th cost of travling along an dg as a function of th flow of various tys of vhicls ovr that dg. W rlax th assumtions ndd for th xistnc of a Nash quilibrium in this htrognous routing gam. W xtnd th availabl rsults to rsnt ncssary and sufficint conditions for th xistnc of a otntial function. W charactriz a st of tolls that guarant th xistnc of a otntial function whn only two tys of usrs ar articiating in th gam. W rsnt an ur bound for th ric of anarchy (i.., th worst-cas ratio of th social cost calculatd for a Nash quilibrium ovr th social cost for a socially otimal flow) for th cas in which only two tys of layrs ar articiating in a gam with affin dg cost functions. A htrognous routing gam with vhicl latooning incntivs is usd as an xaml throughout th articl to clarify th concts and to validat th rsults. 1 Introduction 1.1 Motivation Routing gams ar of scial intrst in transortation ntworks [2 4 and communication ntworks [5 7 bcaus thy allow us to study cass in which a dsirabl global bhavior (.g., achiving a socially otimal solution) can mrg from siml local stratgis (.g., imosing tolls on ach road basd on only local information). For th uros of this articl, routing gams can b dcomosd into two catgoris. In th first catgory, namly, homognous routing gams, drivrs or vhicls ar of th sam ty and, thrfor, xrinc th sam cost whn using an dg in th ntwork. Such an assumtion is rimarily motivatd by transortation ntworks for which th drivrs only worry about th travl tim (and indd undr th assumtion that all th drivrs ar qually snsitiv to latncy through considring thir avrag bhavior) or ackt routing in communication ntworks whr all th ackts that ar using a articular link xrinc th sam dlay or rliability. In th scond catgory, namly, htrognous routing gams (a.k.a., multi-class routing gams [8, 9), drivrs or vhicls blong to mor than on ty du to th following rasons: - Ful Consumtion: In a transortation ntwork, if w includ th ful consumtion of th vhicls in th cost functions, two vhicls (of diffrnt tys) may xrinc diffrnt costs for using a road vn if thir travl tims ar qual. For instanc, [1 studid this hnomnon in atomic congstion gams in which havy-duty vhicls xrinc an incrasd fficincy whn a highr numbr of havy-duty vhicls ar rsnt on th sam road, bcaus of a highr ossibility of latooning and, thrfor, a highr ful fficincy, whil such an incrasd fficincy may not b tru for cars. For an xrimntal study of imrovmnts in th ful fficincy causd by latooning in havy-duty vhicls, s [11. 1 An arly vrsion of this articl was rsntd at th Annual Allrton Confrnc on Communication, Control, and Comuting [1. 2 F. Farokhi and K. H. Johansson ar with ACCESS Linnaus Cntr, School of Elctrical Enginring, KTH Royal Institut of Tchnology, SE-1 44 Stockholm, Swdn. Th work of F. Farokhi and K. H. Johansson was suortd by grants from th Swdish Rsarch Council, th Knut and Alic Wallnbrg Foundation, and th iqflt rojct. s: {farokhi,kallj}@.kth.s 3 W. Krichn is with th dartmnt of Elctrical Enginring and Comutr Scincs, Univrsity of California at Brkly, CA, USA. walid@cs.brkly.du 4 Th work of W. Krichn and A. M. Bayn was suortd by grants from th California Dartmnt of Transortation, Googl, and Nokia. 5 A. M. Bayn is with th dartmnt of Elctrical Enginring and Comutr Scincs, and th dartmnt of Civil and Environmntal Enginring, Univrsity of California at Brkly, CA, USA. bayn@brkly.du 1

2 - Snsitivity to Latncy: It is known that drivrs on a road hav diffrnt snsitivitis to th latncy undr diffrnt circumstancs as wll as dnding on thir rsonality and background [12, 13. In addition, du to conomic advantags, havy-duty vhicls might b mor snsitiv to latncy in comarison to cars (bcaus thy nd to dlivr thir goods at scific tims). - Snsitivity to Tolls: Drivrs gnrally ract diffrntly to road tolls,.g., basd on th rason of th tri or thir socioconomic background. For instanc, in 21, by th rqust of th Swdish Institut for Transort and Communications Analysis, th consulting firm Inrgia comild a survy to stimat th valu of tim for th drivrs in Stockholm [14. According to that study, drivrs valud thir tim as.98, 3.3, and.19 SEK/min for work and school commuting tris, businss tris, and othr tris, rsctivly. Ths xamls motivat our intrst for studying htrognous routing gams in which th drivrs or th vhicls might blong to mor than on ty and thir ty dtrmins th cost of travling along an dg as a function of th flow of all tys of vhicls ovr that dg. 1.2 Rlatd Work In th contxt of transortation ntworks, routing gams wr originally studid in [3. This study also formulatd th dfinition of Nash quilibrium in routing gams 1. Latr, [17 showd that undr som mild conditions, th routing gam admits a otntial function and th minimizrs of this otntial function ar Nash quilibria of th routing gam. This rsult guarants th xistnc of a Nash quilibrium for th routing gam. Th roblm of bounding th infficincy of Nash quilibria has bn xtnsivly studid; s [15, for a survy of ths rsults. Htrognous routing gams hav bn studid xtnsivly ovr th ast starting with ionring works in [8, 9. In ths studis, a routing gam with multi-class usrs wr introducd and th dfinition of quilibrium was givn. Furthrmor, in [9, th author introducd a sufficint condition for transforming th roblm of finding an quilibrium to that of an otimization (i.., quivalnt to th xistnc of a otntial function [23, 24). Th sufficint condition is that ovr ach dg, th incrasd cost of a usr of th first ty du to addition of on mor usr of th scond ty is qual to th incrasd cost of a usr of th scond ty du to addition of on mor usr of th first ty, i.., th usrs of th first and th scond ty influnc ach othr qually [9. This condition was considrd latr in [25 in which it was also notd that satisfaction of this symmtry condition may dnd on th units (.g., tim or mony) adotd for rrsnting th cost functions for th cas in which th usrs tys ar dtrmind by thir valu of tim (i.., a scalar factor that balancs th rlationshi btwn th latncy and th imosd tolls). This rsults is of scial intrst sinc th quilibrium dos not chang by using diffrnt units for th cost functions (if th latncy only dnds on th sum of th flows of various tys ovr th dg, not th individual flows, and th valu of tim aars linarly in th cost functions) [26. Ncssary and sufficint conditions for th xistnc of otntial functions in gams with finit numbr of layrs was rcntly invstigatd in [27; howvr, ths rsults wr not gnralizd to gams with a continuum of layrs as in htrognous routing gams. Th authors in [28 studid th xistnc of an quilibrium in htrognous routing gams vn if such a symmtry condition dos not hold. In contrast to ths articls that assumd a finit st of tys to which th usrs may blong, a walth of studis also considrd th cas in which th usrs may blong to a continuum of tys [29, 3. Th roblm of finding tolls for gnral htrognous routing gams as wll as th cas in which tys of th usrs is dtrmind by thir valu of tim hav bn considrd xtnsivly [ For instanc, in [31, th roblm of dtrmining tolls on ach dg or ath for htrognous routing gams was studid. Guarants wr rovidd for that th socially otimal solution (also rfrrd to as systm-otimizing flow [9) is indd an quilibrium of th gam. Howvr, in that articl, th usrs wr assumd to b qually snsitiv to th imosd tolls. Th roblm of finding otimal tolls for routing gam in which th usrs valu of tim blongs to a continuum was studid in [32. 1 Throughout this articl, following th convntion of [15, 16, w us th trm Nash quilibrium to rfr to this quilibrium. S Rmark 2.1 for mor information rgarding this mattr. 2

3 1.3 Contributions of th Articl In this articl, w formulat a gnral htrognous routing gam in which th vhicls 2 might blong to mor than on ty. Th vhicl s ty dtrmins th maing that scifis th cost for using an dg basd on th flow of all tys of vhicls ovr that dg. W rov that th roblm of charactrizing th st of Nash quilibria for a htrognous routing gam is quivalnt to th roblm of dtrmining th st of ur stratgy Nash quilibria in a gam with finitly many layrs (in which ach layr rrsnts on of th tys in th original htrognous routing gam). Doing so, w can mloy classic rsults in gam thory and conomics litratur, scially rgarding th xistnc of an quilibrium in gams and abstract conomis [37,38 (which is an xtnsion of gams to a situation whr th actions of othr layrs can modify th st of fasibl actions for a layr), to show that undr mild conditions, a htrognous routing gam admits at last on Nash quilibrium. Thn, w rsnt a ncssary condition for th xistnc of a otntial function for th htrognous routing gam. W show that this condition is also sufficint for th cas in which only two tys of layrs ar articiating in th routing gam. In this cas, w show, following th otntial gam litratur [23, that th roblm of finding a Nash quilibrium in th htrognous routing gam can b osd as an otimization roblm (which is numrically tractabl if th otntial function is convx). Motivatd by th sufficint condition, in th rst of this articl, w focus on htrognous routing gams in which only two tys of usrs ar articiating. Not that in contrast to th rsults of [9, 25, hr, w rsnt a ncssary and sufficint condition for th xistnc of otntial function through which minimization w can rcovr an quilibrium. Howvr, th ric of roviding this tightr condition is that w can only trat routing gams with two distinct tys contrary to th sufficint condition in [9, 25. If th roblm of finding a Nash quilibrium in th htrognous routing gam is numrically intractabl 3, it might b unlikly for th drivrs to figur out a Nash quilibrium in finit tim (lt alon an fficint on) and utiliz it. This might rsult in infficint utilization of th transortation ntwork rsourcs. Thrfor, w rsnt a st of tolling olicis for distinguishabl tys (i.., a routing gam in which w may imos diffrnt tolls for diffrnt usr tys) and indistinguishabl tys (i.., whn w cannot imos ty-dndnt tolls) to guarant th xistnc of a otntial function for htrognous routing gams. Th ida of roosing tolls for indistinguishabl tys has bn rviously studid in [42. Howvr, in that study, th tolls wr introducd to minimiz th total travl tim and th total travl cost (as a bi-objctiv otimization roblm). In addition, in [42, th usrs tys corrsondd to socio-conomic charactristics and, thrfor, th cost functions of various tys of usrs wr th latncy (which th function of th total flow and not individual flows of ach ty) lus th tolls multilid by th valu of tim. Finally, bcaus a Nash quilibrium is tyically infficint (i.., it dos not minimiz th social cost function 4 ), w study th ric of anarchy 5 (a masur of th infficincy of a Nash quilibrium which can b dfind as th worst-cas ratio of th social cost at a Nash quilibrium ovr th social cost at a socially otimal flow). W rov that for th cas in which a convx otntial function xists, th ric of anarchy is boundd from abov by two for affin dg cost functions, that is, th social cost of a Nash quilibrium can b at most twic as much as th cost of a socially otimal solution. 1.4 Articl Organization Th rst of th articl is organizd as follows. W formulat th htrognous routing gam in Sction 2. In Sction 3, w rov that a Nash quilibrium may indd xist in this routing gam. W rsnt a st of ncssary and sufficint conditions to guarant th xistnc of a otntial function in Sction 4. In Sction 5, a st of tolling olicis is rsntd to satisfy th aformntiond conditions. 2 W us th trms layrs, drivrs, usrs, and vhicls intrchangably to dnot an infinitsimal art of th flow that stratgically tris to minimiz its own cost for using th road. 3 In gnral, th roblm of finding a ur stratgy Nash quilibrium is not numrically tractabl;.g., [ W us a utilitarian social cost function (i.., summation of th individual cost functions of all th layrs) as oosd to a Rawlsian social cost function (i.., th worst-cas cost function of th layrs); s [43,. 413 for mor information rgarding th diffrnc btwn ths two catgoris of social cost functions. W rsnt th dfinition of th social cost function in Sction 6. 5 Th notion of ric of anarchy was first introducd in [44, 45. Latr, it was utilizd in various gams including routing gams [15, 18,

4 W bound th ric of anarchy for affin cost functions in Sction 6. A numrical xaml motivatd by a htrognous routing gam with latooning incntivs is studid in Sction 7. Finally, w conclud th articl and rsnt dirctions for futur rsarch in Sction 8. 2 A Htrognous Routing Gam 2.1 Notation Lt R and Z dnot th sts of ral and intgr numbrs, rsctivly. Furthrmor, dfin Z ( )a {n Z n ( )a} and R ( )a {x R x ( )a}. For simlicity of rsntation, lt N Z 1. W us th notation N to dnot {1,..., N}. All othr sts ar dnotd by calligrahic lttrs. Scifically, C k consists of all k-tims continuously diffrntiabl functions. Lt X R n b a st such that X. A maing f : X R is calld ositiv dfinit if f(x) for all x X. A st-valud maing f : X Y is said to b continuous at x X if for vry y f(x ) and vry squnc {x k } k N such that lim k x k x, thr xists a squnc {y k } k N such that y k f(x k ) for all k N and lim k y k y. W us th notation G (V, E) to dnot a dirctd grah with vrtx st V and dg st E V V. Each ntry (i, j) E dnots an dg from vrtx i V to vrtx j V. A dirctd ath of lngth z from vrtx i to vrtx j is a st of dgs {(i, i 1 ), (i 1, i 2 ),..., (i z 1, i z )} E such that i i and i z j. 2.2 Problm Formulation W roos an xtnsion of th routing gam introducd in [3 to admit mor than on ty of layrs. To b scific, w assum that th ty of a layr θ blongs to a finit st Θ. Lt us assum that a dirctd grah G (V, E) modls th transortation ntwork and that a st of sourc dstination airs {(s k, t k )} K k for som constant K N ar givn. Each air (s k, t k ) is calld a commodity. W us th notation P k to dnot th st of all admissibl aths ovr th grah G that connct vrtx s k V (i.., th sourc of this commodity) to vrtx t k V (i.., th dstination of this commodity). Lt P K k1 P k. W assum that ach commodity k K nds to transfr a flow qual to (Fk θ) θ Θ R Θ. W us th notation f θ R to dnot th flow of layrs of ty θ Θ that us a givn ath P. W us th notation f (f θ ) P,θ Θ R P Θ to dnot th aggrgat vctor of flows 6. A flow vctor f R P Θ is fasibl if P k f θ Fk θ for all k K and θ Θ. W us th notation F to dnot th st of all fasibl flows. To nsur that th st of fasibl flows is not an mty st, w assum that P k if Fk θ for any θ Θ. Notic that th constraints associatd with ach ty ar indndnt of th rst. Thrfor, th flows of a scific ty can b changd without braking th fasibility of th flows associatd with th rst of th tys. A vhicl of ty θ Θ that travls along an dg E xrincs a cost qual to l θ ((φ θ ) θ Θ), whr for any θ Θ, φ θ dnots th total flow of drivrs of ty θ that ar using this scific dg, i.., φ θ P: f θ. This cost can ncomass aggrgats of th latncy, ful consumtion, tc. For notational convninc, w assum that w can chang th ordr with which th dg flows φ θ aar as argumnts of th cost function l θ ((φ θ ) θ Θ). A drivr of ty θ Θ from commodity k K that uss ath P k (conncting s k to t k ) xrincs a total cost of l θ (f) l θ ((φ θ ) θ Θ). Each layr is an infinitsimal art of th flow that tris to minimiz its own cost (i.., ach layr is inclind to choos th ath that has th last cost). Now, basd on this modl, w can dfin th Nash quilibrium. Dfinition 2.1 (Nash Equilibrium in Htrognous Routing Gams) A flow vctor f (f θ ) P,θ Θ is a Nash quilibrium if for all k K and θ Θ, f θ > for a ath P k imlis that l θ (f) l θ (f) for all P k. Θ }. 6 Not that thr is a on-to-on corrsondnc btwn th lmnts of P Θ and th st of intgrs {1,..., P 4

5 This dfinition imlis that for a commodity k K and ty θ Θ, all aths with a nonzro flow for vhicls of ty θ hav qual costs and th rst (i.., aths with a zro flow for vhicls of ty θ) hav largr or qual costs. Rmark 2.1 Not that various articls us diffrnt nams for th quilibrium such as, usr-otimizing flow [9, 28, Wardro quilibrium [4, 28, 49, Wardro first rincil [4, and Nash quilibrium [15, 16. Th trm Wardro quilibrium is common, scially in transortation litratur, du to th ionring work of [3 as wll as th fact that th trm ur stratgy Nash quilibrium is rimarily utilizd in th contxt of gams with finitly many layrs [49. It is vital to not that th dfinition of Nash quilibrium in this ar is indd diffrnt from that of [49, which shows that by incrasing th numbr of usrs (in a gam with finitly many layrs), th Nash quilibrium convrgs to th Wardro quilibrium undr aroriat assumtions. Throughout this articl, following th convntion of [15, 16, w us th trm Nash quilibrium to rfr to this quilibrium. W mak th following standing assumtion rgarding th dg latncy functions for all th tys. Assumtion 2.1 For all θ Θ and E, th dg cost function l θ satisfis th following rortis: (i) lθ C 1 ; (ii) lθ is ositiv dfinit; (iii) θ l θ (u, (φ θ ) θ Θ\{θ})du is a convx function in φ θ for any givn (φ θ ) θ Θ\{θ}. Assumtion 2.1 (iii) is quivalnt to 7 : (iii) l θ (φ θ, (φ θ ) θ Θ\{θ}) is an incrasing function of φ θ for any givn (φ θ ) θ Θ\{θ}. W start by roving th xistnc of a Nash quilibrium and, thn, study th comutational comlxity of finding such an quilibrium. Howvr, bfor that, w rsnt an xaml of a htrognous routing gam in th nxt subsction. 2.3 Examl: Routing Gam with Platooning Incntivs Lt Θ {c, t}, whr t dnots trucks (or, quivalntly, havy-duty vhicls) and c dnots cars (or, quivalntly, light vhicls). Lt th dg cost functions b charactrizd as l c (φ c, φ t ) ξ (φ c + φ t ), l t (φ c, φ t ) ξ (φ c + φ t ) + ζ (φ c, φ t ), whr maings ξ : R R and ζ : R R R dnot rsctivly th latncy for using dg as a function of th total flow of vhicls ovr that dg and th ful consumtion of trucks as a function of th flow of ach ty. Ths costs imly that cars only obsrv th latncy ξ (φ c + φ t ) whn using th roads (which is only a function of th total flow ovr that dg and not th individual flows of ach ty). Howvr, th cost associatd with trucks ncomasss an additional trm which modls thir ful consumtion. Following this intrrtation, ζ (φ c, φ t ) is a dcrasing function in φ t sinc by having a highr flow of trucks ovr a givn road (i.., largr φ t ) ach truck gts a highr robability for collaboration such as latooning (and as a rsult, a highr chanc of dcrasing its ful consumtion). Lt us giv xamls of ths functions. Basd on th traffic data masurmnts availabl from [3,. 366 (s [1 for a cas study on th rlationshi btwn th avrag vlocity and th numbr of th vhicls on th road in Stockholm), w know that whnvr th traffic on a road is in fr-flow mod, w can modl th avrag vlocity of travling along that road as an affin function of th flow of vhicls ovr that dg according to v (φ c, φ t ) a (φ c + φ t ) + b. 7 Consult [18 for th roof of th quivalnc whn Θ 1. Th roof in th htrognous cas follows th sam lin of rasoning. 5

6 In this modl, b R and a R for E. Thrfor, if th lngth of dg E is qual to L R, w can calculat th latncy of using that dg as ξ (φ c + φ t ) L v (φ c, φ t ) L a (φ c + φ t. ) + b Now, in cass whr a (φ c + φ t ) b, w can us a linarizd 8 modl for th latncy ξ (φ c + φ t ) L L a (φ c + φ t b ). In addition, using [53, w know that th total ful consumtion of a truck which is travling with vlocity v for distanc L ovr a flat road can b modld by ζ (φ c, φ t ) c ( ) L 1 η ng ρ d 2 ρ aa a c D v (φ 2 c, φ t ) + mgc r, (1) whr η ng is th ngin fficincy, ρ d is th nrgy dnsity of disl ful, c D is th air drag cofficint, A a is th frontal ara of th truck, ρ a is th air dnsity, m is th mass of th truck, g is th gravitational acclration, and c r is th th roll rsistanc cofficint. In addition, w hav multilid th ful consumtion by c to balanc th trad-off btwn th latncy and ful consumtion in th aggrgat cost function of th trucks. Following [11, w know that th air drag cofficint c D dcrass if th trucks ar latooning (.g., two idntical trucks can achiv 4.7% 7.7% rduction in th ful consumtion causd by th air drag rduction whn latooning at 7 km/h dnding on th distanc btwn thm). Lt us modl ths changs as c D c D γ(φt ) whr γ : R [, 1 is th robability of forming latoons (which is a function of th flow of trucks φ t ) multilid by th imrovmnts in th air drag cofficint uon latooning. Lt us dfin aramtrs b 2 α L ρ a A a c D 2 η ng ρ d, β L mgc r η ng ρ d. Now, again if w linariz (1) around φ t, w gt ( ζ (φ c, φ t ) c α d ) du γ(u) ub 2 + 2c αγ()b a φ t + (2c αγ()b a ) φ c + ( c β + c αγ()b 2 ). Combing all ths trms rsults in l c (φ c, φ t ) L ( + L ) ( a b b 2 φ c + L ) a b 2 φ t, l t (φ c, φ t ) L ( + c β + c αγ()b 2 + L ) a b b 2 + 2c αγ()b a φ c ( ) + b2 +2c αγ()b a φ t. L a b 2 + c α dγ() du Notic that Assumtion 2.1 (i) and (ii) ar asily satisfid. Howvr, Assumtion 2.1 (iii) is only satisfid if L a b 2 This is indd tru bcaus of th obsrvation that Assumtion 2.1 (iii) and (iii) ar quivalnt. + c α dγ() du b2 + 2c αγ()b a. 3 Existnc of Nash Equilibrium In this sction, w show that th htrognous routing gam admits a Nash quilibrium. Bfor stating th rsult, w nd to introduc som concts from [37 which uss rsults of [38 to rov that an abstract conomy (an xtnsion of a gam) admits an quilibrium undr aroriat conditions 9. 8 Notic that such a linarization is crtainly not valid for a wid rang of traffic flows, howvr, it modls th latncy functions wll-nough for small flows. Th authors in [5, 51 roosd a icwis linar maing (basd on numrical data from th Toronto mtroolitan ara) for modling th latncy as a function of th flow of vhicls. This modl justifis using a linar modl for small flows (i.., at th bginning what thy call th fasibl rgion), howvr, it also oints out that a linar aroximation is not valid for larg flows. For a comrhnsiv comarison of diffrnt latncy maings (linar as wll as nonlinar ons), s [52. 9 Not that w could altrnativly follow th dfinition and rsults of [38 in a dirct mannr, howvr, in that cas, w nd mor background matrial rsntd which might b distracting to th audinc. 6

7 3.1 Existnc of Nash Equilibrium in Gams Lt us dfin an abstract conomy 1 as follows. Lt X i R n (for som n N) dnot th action st of layr i N in an abstract conomy with N layrs. W us th notation x i X i to dnot th action of layr i. In contrast to a gam, th fasibl st of actions that layr i can choos from is a function of actions of othr layrs x i (x j ) j i. Lt Z i : j i X j X i b a st-valud maing that dtrmins th st of fasibl actions for layr i. Th utility of layr i is govrnd by a ral-valud function U i : N j1 X j R. In this stu (oosd to th on rsntd in [37), w assum th layrs ar sking to minimiz thir utility. Dfinition 3.1 (Equilibrium of an Abstract Economy [37) x is an quilibrium oint of an abstract conomy if, for all i N, x i arg min x i Z i(x i ) U i (x i, x i ). For any i N, w say that Z i has a closd grah at x i j i X j if th st {(x j ) j N x i Z i (x i )} is a closd st. Now, w can stat th rsult of [37 rgarding th xistnc of such an quilibrium. Thorm 3.2 ([37) If, for ach i N, X i is a comact convx st, U i (x i, x i ) is continuous on N j1 X j and quasi-convx in x i for ach x i j i X j, Z i is a continuous st-valud maing that has a closd grah, and Z i (x i ) is a nonmty convx st for ach x i j i X j, thn th abstract conomy admits an quilibrium. Not that whn Z i (x i ) X i for all x i j i X j, and all i, w hav a gam with finitly many layrs. Thrfor, an abstract conomy can b considrd as a gnralization of a gam. Dfinition 3.3 (Pur Stratgy Nash Equilibrium in Gams with Finitly Many Playrs [54) x is a ur stratgy Nash quilibrium if, for all i N, x i arg min x i X i U i (x i, x i ). Thorm 3.2 rsults now in th following usful corollary. Corollary 3.4 If, for ach i N, X i is a comact convx st and U i (x i, x i ) is continuous on N j1 X j and quasi-convx in x i for ach x i j i X j, thn th gam admits a ur stratgy Nash quilibrium. Proof: Th roof follows from utilizing Thorm 3.2 whn, for all i N, Z i (x i ) X i for all x i j i X j. With this rsult in hand, w can go ahad and rov th xistnc of a Nash quilibrium in th htrognous routing gam. In th nxt subsction, w first rov that th roblm of finding a Nash quilibrium for th htrognous routing gam is quivalnt to th roblm of finding a ur stratgy Nash quilibrium in an abstract gam 11 with finitly many layrs. Thn, w us Corollary 3.4 to show that this gam admits a Nash quilibrium undr Assumtion Existnc of Nash Equilibrium in Htrognous Routing Gams For th sak of simlicity of rsntation and without loss of gnrality (sinc Θ is finit), w can assum that Θ {θ 1,..., θ N } whr N Θ. Now, lt us dfin th abstract gam. Dfinition 3.5 An abstract gam is a gam with N layrs in which layr i N corrsonds to ty θ i Θ in th htrognous routing gam. Th action of layr i is a i (f θi ) P which blongs to th action st { A i (f θi ) P R P } f θi F θi k. P k 1 An abstract conomy was originally dfind in [37. It is an xtnsion of a gam. 11 W us th trm abstract to mhasiz th fact that th introducd gam dos not hav any hysical intuition and it is simly a mathmatical conct dfind for roving th rsults of this ar. This xrssion should not b confusd with that of an abstract conomy. 7

8 Additionally, th utility of layr i is dfind as U i (a i, a i ) E θ i l θi (u, (φ θj ) θj Θ\{θ i})du, (2) whr a i rrsnts th actions of th rst of th layrs (a j ) j N \{i} and φ θi th dg flow of ty θ i for ach i N. P: f θi is Th following rsult stablishs an intrsting rlationshi btwn th introducd abstract gam and th undrlying htrognous routing gam. Lmma 3.6 A flow vctor (f θ ) P,θ Θ is a Nash quilibrium of th htrognous routing gam if and only if ((f ) P,..., (f θ N ) P) is a ur stratgy Nash quilibrium of th abstract gam. Proof: Notic that ((f ) P,..., (f θ N ) P) bing a ur stratgy Nash quilibrium (s Dfinition 3.3) of th abstract gam is quivalnt to that for all i N, a i (f θi ) P is th bst rsons of layr i to th tul of actions a i ((f θj ) P) θj Θ\{θ i} or, quivalntly, a i arg min (f θ i ) P s.t. E P: θ i f θi f θi P k f θi, P. l θi (u, (φ θj ) θj Θ\{θ i})du, φ θi, E, F θi k, k K, whr φ θj P: f θj for all j N \{i}. Notic that du to Assumtion 2.1 (iii), this roblm is indd a convx otimization roblm. Lt us dfin th Lagrangian as L i ((φ θi ) E, (f θi ) P) E θ i K k1 w i k l θi (u, (φ θj f θi P k ) θj Θ\{θ i})du + v i E F θi k P λ i f θi, P: f θi φ θi whr (v) i E R E, (wk i ) k K R K, and (λ i ) P R P ar Lagrang multilirs. Now, using Karush Kuhn Tuckr thorm [55,. 244, otimality conditions ar and f θi φ θi L i ((φ θi ) E, (f θi ) θi P) l (φ θi, (φ θj ) θj Θ\{θ i}) v i, E, (3) L i ((φ θi ) E, (f θi ) P) ( v i ) w i k λ i, P k, k K. (4) Additionally, th comlimntary slacknss conditions (for inquality constraints) rsult in λ i f i for all P. Hnc, for all k and P k, w hav l θi ((f θ ) P,θ Θ) l θi (φ θi, (φ θj ) θj Θ\{θ i}) v i by (3) w i k + λ i. by (4) 8

9 Thrfor, for any 1, 2 P k, if f θi 1, f θi 2 >, w hav λ θi 1 λ θi 2 (bcaus of th comlimntary slacknss conditions), which rsults in l θi 1 ((f θ ) P,θ Θ) w i k l θi 2 ((f θ ) P,θ Θ). Furthrmor, for any 3 P k such that f θi 3, w gt λ θi 3 (bcaus of dual fasibility, i.., th Lagrang multilirs associatd with inquality constraints must b non-ngativ), which rsults in l θi 3 ((f θ ) P,θ Θ) w i k + λ θi 3 w i k l θi 1 ((f θ ) P,θ Θ). This comlts th roof. Thorm 3.7 Undr Assumtion 2.1, th htrognous routing gam admits at last on Nash quilibrium. Proof: Following th rsult of Lmma 3.6, roving th statmnt of this thorm is quivalnt to showing th fact that th abstract gam introducd in Dfinition 3.5 admits at last on ur stratgy Nash quilibrium. First, notic that for all i N, A i is a non-mty, convx, and comact subst of th Euclidan sac R P. Scond, U i (a i, a i ) is continuous in all its argumnts (bcaus it is dfind as an intgral of a ral-valud masurabl function). Finally, bcaus of Assumtion 2.1 (iii), U i (a i, a i ) is a convx function in a i. Now, it follows from Corollary 3.4 that th abstract gam admits at last on ur stratgy Nash quilibrium. Rmark 3.1 Thorm 3.7 can b sn as an xtnsion of [28. In that study, th authors assum that th cost functions ar monoton, that is, l θ ((φ θ ) θ Θ) l θ θ (( φ ) θ Θ) for all θ Θ if φ θ θ φ if θ Θ; s [28,. 58. This condition, in turn, imlis that l θ ((φ θ ) θ Θ) is a non-dcrasing function of all its argumnts which is strongr than Assumtion 2.1 (iii). 4 Finding a Nash Equilibrium A family of gams that ar rlativly asy to analyz ar otntial gams. In this sction, w giv conditions for whn th introducd abstract gam is a otntial gam. Dfinition 4.1 (Potntial Gam [23) Th abstract gam is a otntial gam with otntial function V : N i1 A i R if for all i N, V (a i, a i ) V (ā i, a i ) U i (a i, a i ) U i (ā i, a i ), a i, ā i A i and a i j N \{i} A j. Th nxt lmma rovids a ncssary condition for th xistnc of a otntial function in C 2. Lmma 4.2 If th abstract gam admits a otntial function V C 2, thn [ l θj φ θi ((φ θ ) θ Θ) l θi φ θj ((φ θ ) θ Θ), 1 2 for all i, j N and 1, 2 P. Proof: Sinc V ((f ) P,..., (f θ N ) P) is a otntial function for th abstract gam, it satisfis, for all i N, V ((f θi ) P, ((f θj ) θi P) θj Θ\{θ i}) V (( f ) P, ((f θj ) P) θj Θ\{θ i}) U i ((f θi ) P, ((f θj ) P) θj Θ\{θ i}) U i (( f θi ) P, ((f θj ) P) θj Θ\{θ i}), 9

10 which rsults in th idntity V ((f θ ) P,θ Θ) f θi 1 V ((f θi lim ɛ U i ((f θi lim ɛ U i((f θ + ɛδ 1 ) P, ((f θj ) P) θj Θ\{θ i}) V ((f θi ) P, ((f θj ) P) θj Θ\{θ i}) + ɛδ ɛ ) 1 P, ((f θj ) P) θj Θ\{θ i}) U i ((f θi ) P, ((f θj ) P) θj Θ\{θ i}) ) P,θ Θ) f θi 1. in which δ ij dnots th Kronckr indx (or dlta) dfind as δ ij 1 if i j and δ ij othrwis. Hnc, w gt V ((f θ ) P,θ Θ) f θi 1 ɛ θ i f θi 1 E 1 lθ i ((φ θ ) θ Θ). l θi (u,(φ θj ) θj Θ\{θ i})du Now, bcaus of Clairaut-Schwarz thorm [56,. 167, w know that th following quality must hold sinc V C 2, 2 V ((f θ ) P,θ Θ) Lt us calculat and, similarly, f θi 1 f θj 2 2 V ((f θ ) P,θ Θ) f θi 1 f θj 2 2 V ((f θ ) P,θ Θ) f θj 2 f θi Substituting (6) and (7) into (8) rsults in [ 1 2 φ θj (5) 2 θ V ((f ) P,θ Θ). (6) f θj 2 f θi 1 f θi 1 f θi 1 [ V ((f θ [ θ l j 1 2 ) P,θ Θ) f θj 2 lθj ((φ θ ) θ Θ) 2 ((φ θ ) θ Θ) φ θi lθi ((φ θ l θi ((φ θ ) θ Θ) φ θi, ) θ Θ) φ θj l θj ((φ θ ) θ Θ) (7). (8) for all 1, 2 P and θ i, θ j Θ. Intrstingly, w can rov that this condition is also a sufficint condition for th xistnc of a otntial function (that blongs to C 2 ) whnvr two tys of layrs ar articiating in th htrognous routing gam. Lmma 4.3 Assum that Θ 2. If [ for all 1, 2 P, thn 1 2 φ V ((f ) P, (f θ2 ) P) E l θ2 (φ, φ θ2 ) [ θ 1 φ θ2 θ 2 θ 1, l (φ, φ θ2 ), l (u 1, φ θ2 )du θ 2 l θ2 (φ, u 2 )du 2 u 2 lθ 1 (u 1, u 2 )du 1 du 2

11 is a otntial function for th abstract gam. Proof: Notic that for all P, w gt V ((f θ ) P,θ Θ) f θ 1 f θ 1 ( E [ θ 1 [ l θ 1 (φ θ 1, φ θ 2 ) + l θ 1 (φ θ 1, φ θ 2 ) + θ φ 2 l θ 1 (u 1, φ θ 2 )du 1+ l θ 2 (φ θ 1, u 2)du 2 θ 2 φ θ 1 θ 2 θ φ 2 θ φ 1 θ φ 2 l θ 2 (φ θ 1, u 2)du 2 1 lθ (φ θ 1, u 2)du 2 u 2 [ φ θ 1 l θ 2 (φ θ 1, u 2) 1 lθ (φ θ 1, u 2) du 2. u 2 u 2 lθ 1 (u 1, u 2)du 1du 2 ) (9) Now, lt us dfin Ψ((φ ) E, (φ θ2 ) E ) θ 2 [ φ l θ2 (φ, u) l (φ, u) du. u W hav Ψ((φ ) E, (φ θ2 ) E ) [ l θ2 f θ2 ˆ φ (φ, φ θ2 ) l (φ, φ θ2 ), ˆ u for all ˆ P. Noticing that φ θ2 ˆ P: ˆ f θ2 ˆ Ψ((φ ) E, (φ θ2 ) E ) Ψ((φ φ θ2 ˆ P: ˆ for all E, w gt ) E, (φ θ2 ) E ), E. Thus, Ψ((φ ) E, (φ θ2 ) E ) Ψ((φ ) E, ). Stting Ψ((φ ) E, (φ θ2 ) E ) (s dfinition abov) insid (9) rsults in V ((f θ ) P,θ Θ) f f θ2 ˆ l (φ, φ θ2 ) U 1((f ) P, (f θ2 f ) P), (1) whr th artial drivativs of U 1 can b comutd from its dfinition in (2). Lt (f ) P and ( f ) P b arbitrary oints in st of actions A 1. Furthrmor, lt r : [, 1 A 1 b a continuously diffrntiabl maing (i.., r C 1 ) such that r() ( f ) P and r(1) (f ) P which rmains insid A 1 R P for all t (, 1). W dfin grah(r) as th collction of all ordrd airs (t, r(t)) for all t [, 1, which dnots a continuous ath that conncts (f ) P and ( f ) P. W know that at last on such maing xists bcaus A 1 is a simly connctd st for all i N. Hnc, w hav [ [ V (a 1, a 2 ) 1 V (a 1, a 2 ) grah(r) a 1 dr r(t) a1r a 1 dt a1r(t) t 1 [ d dt V (r(t), a 2) dt V (r(1), a 2 ) V (r(), a 2 ) V ((f ) P, (f θ2 ) P) V (( f ) P, (f θ2 ) P), 11

12 whr th scond to last quality is a dirct consqunc of th fundamntal thorm of calculus [56, Not that this quality holds irrsctiv of th slctd ath. Thrfor, V ((f ) P, (f θ2 ) P) V (( Similarly, w can also rov f ) P, (f θ2 [ V (a 1, a 2 ) a 1 dr a1r [ U 1 (a 1, a 2 ) a 1 dr by (1) a1r grah(r) grah(r) ) P) U 1 ((f ) P, (f θ2 ) P) U 1 (( f ) P, (f θ2 ) P), V ((f θ ) P,θ Θ) f θ 2 f θ 2 E [ θ φ 1 ( [ θ φ 1 φ θ 2 l θ 1 (u 1, φ θ 2 )du 1+ θ φ 2 l θ 2 (φ θ 1, u 2)du 2 θ l θ 1 (u 1, φ θ 2 )du 1 + l φ 1 θ 2 (φ θ 1, φ θ 2 ) φ θ 2 θ φ 2 θ φ 1 u 2 lθ 1 (u 1, u 2)du 1du 2 ) l θ 1 (u 1, φ θ 2 )du 1 (11) l θ 2 (φ θ 1, φ θ 2 ), which rsults in and, consquntly, V ((f ) P, (f θ2 f θ2 ) P) V ((f ) P, (f θ2 ) P) V ((f ) θ2 P, ( f ) P) l θ2 (φ, φ θ2 ) U 2((f ) P, (f θ2 f θ2 U 2 ((f ) P, (f θ2 ) P) U 2 ((f ) P, ( ) P), f θ2 ) P). This concluds th roof. Now, combing th rvious two lmmas rsults in th main rsult of this sction. Thorm 4.4 Assum that Θ 2. Th abstract gam admits a otntial function V C 2 if and only if [ l θ2 (φ, φ θ2 ) l (φ, φ θ2 ), for all 1, 2 P. 1 2 φ Proof: Th roof asily follows from Lmmas 4.2 and 4.3. Not that th otntial function rsntd in Lmma 4.3 blongs to C 2 du to Assumtion 2.1 (i). Following a basic rorty of otntial gams, it is asy to rov th following corollary which shows that th rocss of finding a Nash quilibrium of th htrognous routing gam is quivalnt to solving an otimization roblm. φ φ θ2 Corollary 4.5 Assum that Θ 2. Furthrmor, lt [ l θ2 (φ, φ θ2 ) φ θ2 l (φ, φ θ2 ), 12

13 for all P. If f (f θ ) P,θ Θ is a solution of th otimization roblm min V ((f ) P, (f θ2 ) P), s.t. f φ and P: f P k P: f θ2 F k and f θ2 P k f, f θ2, P, φ θ2, E, F θ2 k, k K, whr V ((f ) P, (f θ2 ) P) is dfind in Lmma 4.3, thn f (f θ ) P,θ Θ is a Nash quilibrium of th htrognous routing gam. Proof: Th roof is consqunc of th fact that a minimizr of th otntial function is a ur stratgy Nash quilibrium of a otntial gam; s [23. Notic that so far w hav rovd that a minimizr of th otntial function is a Nash quilibrium but not th othr way round. Now, w ar rady to rov this whnvr th otntial function is convx. Corollary 4.6 Lt Θ 2 and φ l θ2 (φ, φ θ2 ) φ θ2 l (φ, φ θ2 ), for all E. Furthrmor, assum that th otntial function V ((f ) P, (f θ2 ) P), dfind in Lmma 4.3, is a convx function. Thn f (f θ ) P,θ Θ is a Nash quilibrium of th htrognous routing gam if and only if it is a solution of th convx otimization roblm min s.t. V ((f ) P, (f θ2 ) P), φ and P: f f P k P: f θ2 F k and f θ2 P k f, f θ2, P. φ θ2, E, F θ2 k, k K, Proof: S Andix A. Rmark 4.1 Not that Corollary 4.6 is rovd at th ric of a mor consrvativ condition bcaus th conditions in Corollary 4.5 rquirs th summation of th diffrncs btwn th drivativs of th cost functions to b qual to zro whil Corollary 4.6 nds th individual diffrncs to b qual to zro. Notic that Corollary 4.6 rovids th sam sufficint condition for charactrizing th st of all quilibria as in [9, 25, but ths rfrncs handl th gnral cas of Θ 2 (scifically, s Proosition 1 and Thorm 1 in [25). Thrfor, w can s that th rsntd condition in Corollary 4.5 is tightr than th rsults of [9,25 (sinc it is also a ncssary condition); howvr, it is only valid for Θ 2 in contrast. 4.1 Examl: Routing Gam with Platooning Incntivs Lt us xamin th imlications of Corollary 4.6 in th routing gam with latooning incntivs in Subsction 2.3. For th linarizd modl, w can asily calculat that l c (φ c, φ t ) φ t L a /b 2, (12) l t (φ c, φ t ) φ c L a /b 2 + 2c αγ()b a L a /b 2 + 2c αb a. (13) 13

14 whr th scond quality follows from γ () 1, which holds bcaus from th dfinition of th maing γ : R [, 1, w know that in this cas (i.., whn no trucks ar using that dg) th air drag cofficint is qual to its nominal valu. Thrfor, th condition of Corollary 4.6 dos not hold (unlss c ). Noting that if th roblm of finding a Nash quilibrium in th htrognous routing gam is numrically intractabl, it might b highly unlikly for th drivrs to figur out a Nash quilibrium in rasonabl tim (lt alon an fficint on) and utiliz it, which might rsult in wasting arts of th transortation ntwork rsourcs. Thrfor, a natural qustion that coms to mind is whthr it is ossibl to guarant th xistnc of a otntial function for a htrognous routing gam by imosing aroriat tolls. 5 Imosing Tolls to Guarant th Existnc of a Potntial Function 5.1 Dfinition and Rsults Lt us assum that a vhicl of ty θ Θ must ay a toll τ θ ((φ θ ) θ Θ) for using an dg E, whr φ θ P: f θ. Thrfor, a vhicl using ath P k ndurs a total cost of l θ (f)+τ θ (f), whr τ (f) is th total amount of mony that th vhicl must ay for using ath and can b calculatd as τ θ (f) τ θ ((φ θ ) θ Θ). Th dfinition of a Nash quilibrium is slightly modifid to account for th tolls. Dfinition 5.1 (Nash Equilibrium in Htrognous Routing Gam with Tolls) A flow vctor f (f θ ) P,θ Θ is a Nash quilibrium for th routing gam with tolls if, for all k K and θ Θ, whnvr f θ > for som ath P k, thn l θ (f) + τ θ (f) l θ (f) + τ θ (f) for all P k. Bfor stating th main rsult of this sction, not that w can hav both distinguishabl and indistinguishabl tys. This charactrization is of scial intrst whn considring th imlmntation of tolls. For distinguishabl tys, w can imos individual tolls for ach ty. Howvr, for indistinguishabl tys, th tolls ar indndnt of th ty. To giv an xaml, if Θ {cars, trucks}, w can imos diffrnt tolls for ach grou of vhicls whil if Θ {atint drivrs, imatint drivrs}, w cannot. Notic that in th cas of indistinguishabl tys, on might argu that w cannot masur φ θi for ach θ i Θ individually (bcaus as w motivatd th ty of usr may not b idntifid from hysical traits). Howvr, w can us survys and historical data to xtract th statistics of ach ty (.g, to raliz what ratio of th actual flow blongs to ach ty) but whn calculating th tolls for ach usr w cannot forc that usr to articiat in a survy. W trat ths two cass saratly. Proosition 5.2 (Distinguishabl Tys) Assum that Θ 2. Th abstract gam admits th otntial function if V ((f ) P, (f θ2 ) P) E + [ θ 1 θ 2 θ 2 θ 1 ( l (u 1, φ θ2 ( l θ2 (φ ) + τ, u 2 ) + τ θ2 (u 1, φ θ2 ))du 1 (φ, u 2 ))du 2 u 2 ( l (u 1, u 2 ) + τ (u 1, u 2 ))du 1 du 2 for all E. τ (φ, φ θ2 ) φ θ2 θ2 τ (φ, φ θ2 θ2 ) l φ (φ, φ θ2 φ ) l (φ, φ θ2 φ θ2 ), Proof: S Andix B. 14

15 Proosition 5.3 (Indistinguishabl Tys) Assum that Θ 2. Th abstract gam admits th otntial function V C 2 in Proosition 5.2 with τ (φ, φ θ2 ) τ θ2 (φ, φ θ2 ) τ (φ, φ θ2 ) if for all E. τ (φ, φ θ2 ) φ θ2 τ (φ, φ θ2 θ2 ) l φ (φ, φ θ2 φ ) l (φ, φ θ2 φ θ2 ), Proof: Th roof immdiatly follows from using Proosition 5.2 with th constraint that th tolls may not dnd on th ty, i.., τ (φ, φ θ2 ) τ θ2 (φ, φ θ2 ) τ (φ, φ θ2 ). In gnral, w can rov th following corollary concrning th ty-indndnt tolls. Corollary 5.4 ( Indistingushabl Tys) Assum that Θ 2. Th abstract gam admits a otntial function V C 2 if th imosd tolls ar of th following form τ (φ, φ θ2 ) c + θ 2 f (q, φ + φ θ2 q)dq + ψ (φ + φ θ2 ), whr c R, ψ C 1, and f (x, y) l θ2 (y, x)/y l (y, x)/x for all E. Proof: S Andix C. Throughout this subsction, w assumd that all th drivrs ortray similar snsitivity to th imosd tolls. This is indd a sourc of consrvatism, scially whn daling with routing gams in which th htrognity is causd by th fact that th drivrs ract diffrntly to th imosd tolls. Crtainly, an avnu for futur rsarch is to dvlo tolls for a mor gnral stu. 5.2 Examl: Routing Gam with Platooning Incntivs Lt us xamin th ossibility of finding a st of tolls that satisfis th conditions of Proositions 5.2 and 5.3 for th htrognous routing gam introducd in Subsction 2.3. Distinguishabl Tys-Cas 1: Substituting (12) and (13) into th condition of Proosition 5.2 rsults in τ c (φ c, φ t ) φ t τ t (φ c, φ t ) φ c 2c αb a. (14) Following siml algbraic calculations, w can chck that th tolls τ c (φ c, φ t ) and τ t (φ c, φ t ) (2c αb a )φ c satisfy (14). Noticing that τ t (φ c, φ t ) bcaus by dfinition a R, ths trms can b intrrtd as subsidis aid to th trucks to comnsat for th ful that is wastd du to rsnc of th cars on that scific dg. Distinguishabl Tys-Cas 2: Anothr xaml of aroriat tolls is τ t (φ c, φ t ) and τ c (φ c, φ t ) ( 2c αb a )φ t. Now, w hav τ c (φ c, φ t ). In this cas, th cars ay dirctly for th incrasd ful consumtion of th trucks and, thrfor, thy ar inclind to travl along th dgs that trucks do not us. Indistinguishabl Tys: For this cas, using Corollary 5.4, it is asy to s that tolls τ (φ c, φ t ) (2c αb a )φ t work fin. W us ths tolls in th numrical xaml dvlod in Sction 7. 6 Pric of Anarchy for Affin Cost Functions In th routing gam litratur, it is a widly known fact that gnrally, a Nash quilibrium is infficint vn whn daling with homognous routing gams; s [15, 18, 22. To quantify this infficincy, many studis hav usd Pric of Anarchy (PoA) as a mtric. 15

16 6.1 Social Cost Function First, lt us dfin th social cost of a flow vctor f (f θ ) P,θ Θ as C(f) f θ l θ (f) P θ Θ φ θ l θ ((φ θ ) θ Θ), E θ Θ whr th scond quality can b asily obtaind by rarranging th trms. Using this social cost, w can dfin th otimal flow that w will us latr for comarison with th Nash quilibrium. Dfinition 6.1 (Socially Otimal Flow) f F is a socially otimal flow if C(f) C( f) for all f F. Dfinition 6.2 (PoA) Th ric of anarchy is dfind as PoA C(f Nash ) su f Nash N min f F C(f), whr N dnots th st of Nash quilibria of th htrognous routing gam. In this dfinition, w follow th convntion that Bounding th Pric of Anarchy for Two Tys with Affin Cost Functions Hr, w rsnt an ur bound for th infficincy of th Nash quilibrium in htrognous routing gams whn Θ 2. Th dg cost functions ar takn to b affin functions of th form l (φ, φ θ2 ) αθ 1θ 1 φ + αθ 1θ 2 φ θ2 + βθ 1, l θ2 (φ, φ θ2 ) αθ 2θ 1 φ + αθ 2θ 2 φ θ2 + βθ 2, whr αθ 1θ 1, αθ 1θ 2, αθ 2θ 1, αθ 2θ 2, βθ 1, βθ 2 R ar aramtrs of th routing gam for ach dg E. Notic that th condition αθ 1θ 1, αθ 1θ 2, αθ 2θ 1, αθ 2θ 2 R imlis that th cost of using an dg is incrasing in ach flow saratly (i.., whn a drivr of any ty switchs to an dg, sh cannot dcras th cost of th usrs on this nw dg) whil βθ 1, βθ 2 R imlis that th starting cost of using a road is non-ngativ. This assumtion is crtainly strongr than Assumtion 2.1. Subsction 2.3 rsnts a motivating xaml for affin cost functions. Thorm 6.3 Lt for all E. Thn, PoA 2. αθ 2θ 1 αθ 1θ 2 (15a) [ α θ 1 αθ 1θ 2 αθ 2θ 1 αθ, (15b) 2θ 2 Proof: First, not that if αθ 2θ 1 αθ 1θ 2 for all E, th condition of Corollary 4.5 is satisfid. Thrfor, w can asily calculat th otntial function as V (f) [ 1 2 α θ 1 θ 1 (φ θ 1 ) 2 +(αθ 1 θ 2 φ θ 2 +βθ 1 )φ θ α θ 2 θ 2 (φ θ 2 ) 2 + (αθ 2 θ 1 φ θ 1 + βθ 2 )φ θ 2 αθ 1 θ 2 φ θ 1 φ θ 2 E [ 1 2 φθ 1 l θ 1 (φ θ 1, φ θ 2 ) β θ 1 φ θ φθ 2 l θ 2 (φ θ 1, φ θ 2 ) β θ 2 φ θ 2 (16) E 1 2 C(f) + [ 1 βθ 2 1 φ θ 1 + βθ 2 φ θ 2, E Furthrmor, following th argumnt of [55,. 71, w know that th social cost function is a convx function if and only if (15b) is satisfid. Notic that (16) shows that th otntial function V is a convx function if th social cost function C is a convx function (bcaus th summation of a 16

17 Tabl 1: Paramtrs of th htrognous routing gam in th numrical xaml α aa α at α tt β a β t convx function and a linar function is a convx function). Lt us us f and f to dnot th Nash quilibrium and th socially otimal flow, rsctivly. Now, w can rov inquality C( f) 2V ( f) by (16) and βθ 1, βθ 2 R 2V (f) by Corollary ( θ φ 1 θ φ 2 l θ 1 (u 1, φ θ 2 )du 1 + l θ 2 (φ θ 1, u 2)du 2 E θ φ 2 θ φ 1 ) u l θ 1 (t, u)dtdu by Dfinition of V ( θ φ 1 θ φ 2 l θ 1 (u 1, φ θ 2 )du 1 + by αθ 1 θ 2, αθ 2 θ 1 R 2 E ( 2 2 E θ φ 1 + ( E E 2C(f). θ 2 [ l θ 1 (u 1, φ θ 2 [ l θ 2 (φ θ 1 l θ 2 (φ θ 1, u 2)du 2 ) ) + u 1 1 lθ (u 1, φ θ 2 u 1, u 2) + u 2 2 lθ (φ θ 1 u 2 φ θ 1 l θ 1 (φ θ 1, φ θ 2 ) + φ θ 2 l θ 2 (φ θ 1, φ θ 2 ) E ) du 1 ), u 2) du 2 ) by α θ 1 θ 1, α θ 2 θ 2 R (17) This comlts th roof. Notic that in many ractical situations (such as th on rsntd in Subsction 4.1 for routing gams with latooning incntivs), αθ 2θ 1 αθ 1θ 2. Thrfor, w may not b abl to us Thorm 6.3 to find an ur bound for th PoA. Howvr, as also discussd in Sction 5, in som cass, w might b abl to maniulat ths gains through aroriat tolls to mak sur (15a) holds. In addition, condition (15b) is quivalnt to th condition that αθ 1θ 1 αθ 2θ 2 αθ 2θ 1 αθ 1θ 2 for all E. This condition intuitivly mans that cost function of ach ty of vhicls is mor influncd by th flow of its own ty than th flow of th othr ty. This condition may not hold in gnral in transortation ntworks. In such cas, instad of using Corollary 4.6, w may us Corollary 4.5 in th roof of Thorm 6.3 (that is th only lac that w us th convxity of th otntial function which w rovd using th convxity of th social dcision function). Howvr, doing so, w cannot bound th ratio C(f Nash )/ min f C(f) for all f Nash N. Thrfor, instad of showing that PoA is boundd from abov by two, w can thn only show that th Pric of Stability 12 is ur boundd by two (bcaus w can show that th ratio is boundd by two for only on Nash quilibrium and not for all Nash quilibria). 7 Numrical Examl In this sction, w rsnt a numrical xaml motivatd by th routing gam with latooning incntivs in Subsction 2.3. W us th grah G (V, E) in Figur 1. W hav thr commoditis (s 1, t 1 ) (, 1), (s 2, t 2 ) (2, 3), and (s 3, t 3 ) (7, 8). Th corrsonding aths for th commoditis ar P 1 {{ 1 },{ 2, 4, 3 },{ 2, 7, 5 }}, P 2 {{ 1 },{ 9, 7, 8 },{ 9, 4, 6 }}, P 3 {{ 11, 1, },{ 11, 9, 7, 8, },{ 11, 9, 4, 6, }}. 12 Pric of Stability (PoS), or commonly known as th otimistic Pric of Anarchy, is dfind as inf f Nash N C(f Nash )/ min f F C(f); not that w us inf orator instad of su orator in this dfinition in contrast to that of Dfinition 6.2. S [57 for mor xlanation rgarding th diffrnc btwn PoS and PoA. 17

18 Figur 1: Transortation ntwork in th numrical xaml. Th dg cost functions ar takn to b affin functions of th form l c i (φ c i, φ t i ) α cc (i) φ c i + ᾱ (i) ct φ t i + β c (i), l t i (φ c i, φ t i ) α (i) tc φ c i + ᾱ (i) tt φ t i + β (i) t, whr th dfinitions and th hysical intuition of th aramtrs α (i) cc, α (i) tc, ᾱ (i) tt, ᾱ (i) ct, β c (i), β (i) t can b found in Subsction 2.3. Rcalling that ᾱ (i) tc ᾱ (i) ct (s Subsction 4.1), th condition of Corollary 4.5 is not satisfid. Thrfor, w us th tax τ i (φ c i, φ t i ) (2c αb a )φ t i which is dvlod in Subsction 5.2. This rsults in l c i (φ c i, φ t i ) + τ i (φ c i, φ t i ) α (i) cc φ c i + α (i) ct φ t i + β (i) c, whr α (i) ct function as 11 [ 1 V l t i (φ c i, φ t i ) + τ i (φ c i, φ t i ) α (i) tc φ c i + α (i) tt φ t i + β (i) t, ᾱ (i) ct + 2c αb a and α (i) tt i 2 α(i) cc (φ c i ) 2 +(α (i) ct φ t i +β (i) ᾱ (i) tt + 2c αb a. In this cas, w can calculat th otntial c )φ c i α (i) ct φ c i φ t i α(i) tt (φ t i ) 2 + (α (i) tc φ c i + β (i) t )φ t i. Noticing that solving a non-convx quadratic rogramming roblm might b numrically intractabl in gnral, w focus on th cas in which th otntial function is a convx function. Following th argumnt of [55,. 71, w know that th otntial function is a convx function if and only if [ α cc (i) 1 2 α(i) tc 1 2 α(i) ct α (i) tt, i {,..., 11}. Lt us ick th aramtrs for th routing gam according to Tabl 1. Furthrmor, w choos (F1 a, F1 b ) (5, 1), (F2 a, F2 b ) (3, 3), and (F3 a, F3 b ) (2, 4). Aftr solving th otimization roblm in Corollary 4.5, w can xtract th ath flows and ath cost functions shown in Tabl 2 which dmonstrat a Nash quilibrium (s Dfinition 5.1) 13. In addition, w can calculat C(f) C(f Ur Bound of th PoA, ) whr f dnots th socially otimal flow. This shows that th social cost of th rcovrd Nash quilibrium is only tims th cost of th socially otimal solutions. 8 Conclusions In this articl, w roosd a htrognous routing gam in which th layrs may blong to mor than on ty. Th ty of ach layr dtrmins th cost of using an dg as a function of th flow of all tys ovr that dg. W rovd that this htrognous routing gam admits at last on Nash quilibrium. Additionally, w gav a ncssary and sufficint condition for th xistnc of a otntial function, which indd imlis that w can transform th roblm of finding a Nash quilibrium into an otimization roblm. Finally, w dvlod tolls to guarant th xistnc of a otntial function. Possibl futur rsarch will focus on gnralizing ths rsults to highr numbr of tys or a continuum of layr tys. 13 S htt://dl.drobox.com/u/ /htrognousroutinggam.zi for th Python cod to simulat this numrical xaml. 18

19 Tabl 2: Th ath flow and ath cost function at a Nash quilibrium xtractd by minimizing th otntial function. f c f t P P P l c (f) lt (f) P P P Rfrncs [1 F. Farokhi, W. Krichn, A. M. Bayn, and K. H. Johansson, A htrognous routing gam, in Procdings of th Annual Allrton Confrnc on Communication, Control, and Comuting, 213. [2 C. S. Fisk, Gam thory and transortation systms modlling, Transortation Rsarch Part B: Mthodological, vol. 18, no. 4 5, , [3 J. G. Wardro, Som thortical ascts of road traffic rsarch, in Procdings of th Institut of Civil Enginrs: Enginring Divisions, no. 3, , [4 M. J. Smith, Th xistnc, uniqunss and stability of traffic quilibria, Transortation Rsarch Part B: Mthodological, vol. 13, no. 4, , [5 R. Bannr and A. Orda, Bottlnck routing gams in communication ntworks, IEEE Journal on Slctd Aras in Communications, vol. 25, no. 6, , 27. [6 E. Altman, T. Boulogn, R. El-Azouzi, T. Jiménz, and L. Wyntr, A survy on ntworking gams in tlcommunications, Comutrs & Orations Rsarch, vol. 33, no. 2, , 26. [7 A. Czumaj, Slfish routing on th intrnt, in Handbook of Schduling: Algorithms, Modls, and Prformanc Analysis (J. Y.-T. Lung, d.), Chaman & Hall/CRC Comutr & Information Scinc Sris, CRC Prss, 24. [8 M. Nttr, Equilibrium and marginal cost ricing on a road ntwork with svral traffic flow tys, in Procdings of th 5th Intrnational Symosium on th Thory of Traffic Flow and Transortation, , [9 S. C. Dafrmos, Th traffic assignmnt roblm for multiclass-usr transortation ntworks, Transortation Scinc, vol. 6, no. 1, , [1 F. Farokhi and K. H. Johansson, A gam-thortic framwork for studying truck latooning incntivs, in Procdings of th 16th Intrnational IEEE Annual Confrnc on Intllignt Transortation Systms, , 213. [11 A. A. Alam, A. Gattami, and K. H. Johansson, An xrimntal study on th ful rduction otntial of havy duty vhicl latooning, in Procdings of th 13th Intrnational IEEE Confrnc on Intllignt Transortation Systms, , 21. [12 E. Strn and H. W. Richardson, Bhavioural modlling of road usrs: currnt rsarch and futur nds, Transort Rviws, vol. 25, no. 2, , 25. [13 E. Strn, Ractions to congstion undr tim rssur, Transortation Rsarch Part C: Emrging Tchnologis, vol. 7, no. 2 3,. 75 9,

A Heterogeneous Routing Game

A Heterogeneous Routing Game A Htrognous Routing Gam Farhad Farohi Walid Krichn Alxandr M. Bayn and Karl H. Johansson Abstract Most litratur on routing gams ma th assumtion that drivrs or vhicls ar of th sam ty and hnc xrinc th sam

More information

Network Congestion Games

Network Congestion Games Ntwork Congstion Gams Assistant Profssor Tas A&M Univrsity Collg Station, TX TX Dallas Collg Station Austin Houston Bst rout dpnds on othrs Ntwork Congstion Gams Travl tim incrass with congstion Highway

More information

INCOMPLETE KLOOSTERMAN SUMS AND MULTIPLICATIVE INVERSES IN SHORT INTERVALS. xy 1 (mod p), (x, y) I (j)

INCOMPLETE KLOOSTERMAN SUMS AND MULTIPLICATIVE INVERSES IN SHORT INTERVALS. xy 1 (mod p), (x, y) I (j) INCOMPLETE KLOOSTERMAN SUMS AND MULTIPLICATIVE INVERSES IN SHORT INTERVALS T D BROWNING AND A HAYNES Abstract W invstigat th solubility of th congrunc xy (mod ), whr is a rim and x, y ar rstrictd to li

More information

SCHUR S THEOREM REU SUMMER 2005

SCHUR S THEOREM REU SUMMER 2005 SCHUR S THEOREM REU SUMMER 2005 1. Combinatorial aroach Prhas th first rsult in th subjct blongs to I. Schur and dats back to 1916. On of his motivation was to study th local vrsion of th famous quation

More information

Supplementary Materials

Supplementary Materials 6 Supplmntary Matrials APPENDIX A PHYSICAL INTERPRETATION OF FUEL-RATE-SPEED FUNCTION A truck running on a road with grad/slop θ positiv if moving up and ngativ if moving down facs thr rsistancs: arodynamic

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

arxiv: v3 [cs.gt] 1 Jan 2019

arxiv: v3 [cs.gt] 1 Jan 2019 Pric of Anarchy in Ntworks with Htrognous Latncy Functions Sanjiv Kapoor and Junghwan Shin arxiv:407.299v3 [cs.gt] Jan 209 Abstract W addrss th prformanc of slfish ntwork routing in multi-commodity flows

More information

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013 18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:

More information

Einstein Equations for Tetrad Fields

Einstein Equations for Tetrad Fields Apiron, Vol 13, No, Octobr 006 6 Einstin Equations for Ttrad Filds Ali Rıza ŞAHİN, R T L Istanbul (Turky) Evry mtric tnsor can b xprssd by th innr product of ttrad filds W prov that Einstin quations for

More information

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM Elctronic Journal of Diffrntial Equations, Vol. 2003(2003), No. 92, pp. 1 6. ISSN: 1072-6691. URL: http://jd.math.swt.du or http://jd.math.unt.du ftp jd.math.swt.du (login: ftp) LINEAR DELAY DIFFERENTIAL

More information

1 Input-Output Stability

1 Input-Output Stability Inut-Outut Stability Inut-outut stability analysis allows us to analyz th stability of a givn syst without knowing th intrnal stat x of th syst. Bfor going forward, w hav to introduc so inut-outut athatical

More information

cycle that does not cross any edges (including its own), then it has at least

cycle that does not cross any edges (including its own), then it has at least W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th

More information

WHAT LIES BETWEEN + AND (and beyond)? H.P.Williams

WHAT LIES BETWEEN + AND (and beyond)? H.P.Williams Working Par LSEOR 10-119 ISSN 2041-4668 (Onlin) WHAT LIES BETWEEN + AND (and byond)? HPWilliams London School of Economics hwilliams@lsacuk First ublishd in Grat Britain in 2010 by th Orational Rsarch

More information

Computing and Communications -- Network Coding

Computing and Communications -- Network Coding 89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc

More information

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming CPSC 665 : An Algorithmist s Toolkit Lctur 4 : 21 Jan 2015 Lcturr: Sushant Sachdva Linar Programming Scrib: Rasmus Kyng 1. Introduction An optimization problm rquirs us to find th minimum or maximum) of

More information

DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P

DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P Tsz Ho Chan Dartmnt of Mathmatics, Cas Wstrn Rsrv Univrsity, Clvland, OH 4406, USA txc50@cwru.du Rcivd: /9/03, Rvisd: /9/04,

More information

The Application of Phase Type Distributions for Modelling Queuing Systems

The Application of Phase Type Distributions for Modelling Queuing Systems Th Alication of Phas Ty Distributions for Modlling Quuing Systms Eimutis VAAKEVICIUS Dartmnt of Mathmatical Rsarch in Systms Kaunas Univrsity of Tchnology Kaunas, T - 568, ithuania ABSTRACT Quuing modls

More information

Chapter 10. The singular integral Introducing S(n) and J(n)

Chapter 10. The singular integral Introducing S(n) and J(n) Chaptr Th singular intgral Our aim in this chaptr is to rplac th functions S (n) and J (n) by mor convnint xprssions; ths will b calld th singular sris S(n) and th singular intgral J(n). This will b don

More information

ECE602 Exam 1 April 5, You must show ALL of your work for full credit.

ECE602 Exam 1 April 5, You must show ALL of your work for full credit. ECE62 Exam April 5, 27 Nam: Solution Scor: / This xam is closd-book. You must show ALL of your work for full crdit. Plas rad th qustions carfully. Plas chck your answrs carfully. Calculators may NOT b

More information

Higher order derivatives

Higher order derivatives Robrto s Nots on Diffrntial Calculus Chaptr 4: Basic diffrntiation ruls Sction 7 Highr ordr drivativs What you nd to know alrady: Basic diffrntiation ruls. What you can larn hr: How to rpat th procss of

More information

CS 361 Meeting 12 10/3/18

CS 361 Meeting 12 10/3/18 CS 36 Mting 2 /3/8 Announcmnts. Homwork 4 is du Friday. If Friday is Mountain Day, homwork should b turnd in at my offic or th dpartmnt offic bfor 4. 2. Homwork 5 will b availabl ovr th wknd. 3. Our midtrm

More information

PARTITION HOLE DESIGN FOR MAXIMIZING OR MINIMIZING THE FUNDAMENTAL EIGENFREQUENCY OF A DOUBLE CAVITY BY TOPOLOGY OPTIMIZATION

PARTITION HOLE DESIGN FOR MAXIMIZING OR MINIMIZING THE FUNDAMENTAL EIGENFREQUENCY OF A DOUBLE CAVITY BY TOPOLOGY OPTIMIZATION ICSV4 Cns Australia 9- July, 007 PARTITION HOLE DESIGN FOR MAXIMIZING OR MINIMIZING THE FUNDAMENTAL EIGENFREQUENCY OF A DOUBLE CAVITY BY TOPOLOGY OPTIMIZATION Jin Woo L and Yoon Young Kim National Crativ

More information

Equidistribution and Weyl s criterion

Equidistribution and Weyl s criterion Euidistribution and Wyl s critrion by Brad Hannigan-Daly W introduc th ida of a sunc of numbrs bing uidistributd (mod ), and w stat and prov a thorm of Hrmann Wyl which charactrizs such suncs. W also discuss

More information

2008 AP Calculus BC Multiple Choice Exam

2008 AP Calculus BC Multiple Choice Exam 008 AP Multipl Choic Eam Nam 008 AP Calculus BC Multipl Choic Eam Sction No Calculator Activ AP Calculus 008 BC Multipl Choic. At tim t 0, a particl moving in th -plan is th acclration vctor of th particl

More information

Week 3: Connected Subgraphs

Week 3: Connected Subgraphs Wk 3: Connctd Subgraphs Sptmbr 19, 2016 1 Connctd Graphs Path, Distanc: A path from a vrtx x to a vrtx y in a graph G is rfrrd to an xy-path. Lt X, Y V (G). An (X, Y )-path is an xy-path with x X and y

More information

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1 Chaptr 11 Th singular sris Rcall that by Thorms 10 and 104 togthr provid us th stimat 9 4 n 2 111 Rn = SnΓ 2 + on2, whr th singular sris Sn was dfind in Chaptr 10 as Sn = q=1 Sq q 9, with Sq = 1 a q gcda,q=1

More information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

Free Software Offer and Software Diffusion: The Monopolist Case

Free Software Offer and Software Diffusion: The Monopolist Case Association for Information Systms AIS Elctronic Library (AISL) ICIS 3 Procdings Intrnational Confrnc on Information Systms (ICIS) Dcmbr 3 Fr Softwar Offr and Softwar Diffusion: h Monoolist Cas Zhngrui

More information

Derangements and Applications

Derangements and Applications 2 3 47 6 23 Journal of Intgr Squncs, Vol. 6 (2003), Articl 03..2 Drangmnts and Applications Mhdi Hassani Dpartmnt of Mathmatics Institut for Advancd Studis in Basic Scincs Zanjan, Iran mhassani@iasbs.ac.ir

More information

On the irreducibility of some polynomials in two variables

On the irreducibility of some polynomials in two variables ACTA ARITHMETICA LXXXII.3 (1997) On th irrducibility of som polynomials in two variabls by B. Brindza and Á. Pintér (Dbrcn) To th mmory of Paul Erdős Lt f(x) and g(y ) b polynomials with intgral cofficints

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim (implicit in notation and n a positiv intgr, lt ν(n dnot th xponnt of p in n, and U(n n/p ν(n, th unit

More information

Limiting value of higher Mahler measure

Limiting value of higher Mahler measure Limiting valu of highr Mahlr masur Arunabha Biswas a, Chris Monico a, a Dpartmnt of Mathmatics & Statistics, Txas Tch Univrsity, Lubbock, TX 7949, USA Abstract W considr th k-highr Mahlr masur m k P )

More information

Exam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator.

Exam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator. Exam N a m : _ S O L U T I O N P U I D : I n s t r u c t i o n s : It is important that you clarly show your work and mark th final answr clarly, closd book, closd nots, no calculator. T i m : h o u r

More information

COMPUTER GENERATED HOLOGRAMS Optical Sciences 627 W.J. Dallas (Monday, April 04, 2005, 8:35 AM) PART I: CHAPTER TWO COMB MATH.

COMPUTER GENERATED HOLOGRAMS Optical Sciences 627 W.J. Dallas (Monday, April 04, 2005, 8:35 AM) PART I: CHAPTER TWO COMB MATH. C:\Dallas\0_Courss\03A_OpSci_67\0 Cgh_Book\0_athmaticalPrliminaris\0_0 Combath.doc of 8 COPUTER GENERATED HOLOGRAS Optical Scincs 67 W.J. Dallas (onday, April 04, 005, 8:35 A) PART I: CHAPTER TWO COB ATH

More information

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM Jim Brown Dpartmnt of Mathmatical Scincs, Clmson Univrsity, Clmson, SC 9634, USA jimlb@g.clmson.du Robrt Cass Dpartmnt of Mathmatics,

More information

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter WHEN THE CRAMÉR-RAO INEQUALITY PROVIDES NO INFORMATION STEVEN J. MILLER Abstract. W invstigat a on-paramtr family of probability dnsitis (rlatd to th Parto distribution, which dscribs many natural phnomna)

More information

Large time asymptotics for partially dissipative hyperbolic systems

Large time asymptotics for partially dissipative hyperbolic systems Larg tim asymtotics for artially dissiativ hyrbolic systms K. Bauchard, E. Zuazua Abstract This work is concrnd with (n-comonnt) hyrbolic systms of balanc laws in m sac dimnsions. First w considr linar

More information

Performance analysis of some CFAR detectors in homogeneous Pearson-distributed clutter

Performance analysis of some CFAR detectors in homogeneous Pearson-distributed clutter SETIT 5 3 rd Intrnational Confrnc: Scincs of Elctronic, Tchnologis of Information and Tlcommunications arch 7-31, 5 TNISIA Prformanc analysis of som CFAR dtctors in homognous Parson-distributd cluttr iani

More information

Thinking outside the (Edgeworth) Box

Thinking outside the (Edgeworth) Box Tinking outsid t (dgwort) ox by Jon G. Rily Dartmnt of conomics UCL 0 Novmbr 008 To dvlo an undrstanding of Walrasian quilibrium allocations, conomists tyically start wit t two rson, two-commodity xcang

More information

Exercise 1. Sketch the graph of the following function. (x 2

Exercise 1. Sketch the graph of the following function. (x 2 Writtn tst: Fbruary 9th, 06 Exrcis. Sktch th graph of th following function fx = x + x, spcifying: domain, possibl asymptots, monotonicity, continuity, local and global maxima or minima, and non-drivability

More information

2.3 Matrix Formulation

2.3 Matrix Formulation 23 Matrix Formulation 43 A mor complicatd xampl ariss for a nonlinar systm of diffrntial quations Considr th following xampl Exampl 23 x y + x( x 2 y 2 y x + y( x 2 y 2 (233 Transforming to polar coordinats,

More information

SOME ELEMENTARY PROPERTIES OF THE DISTRIBUTION OF THE NUMBERS OF POINTS ON ELLIPTIC CURVES OVER A FINITE PRIME FIELD

SOME ELEMENTARY PROPERTIES OF THE DISTRIBUTION OF THE NUMBERS OF POINTS ON ELLIPTIC CURVES OVER A FINITE PRIME FIELD SOME ELEMENTARY PROPERTIES OF THE DISTRIBUTION OF THE NUMBERS OF POINTS ON ELLIPTIC CURVES OVER A FINITE PRIME FIELD SAIYING HE AND J MC LAUGHLIN Abstract Lt 5 b a rim and for a, b F, lt E a,b dnot th

More information

That is, we start with a general matrix: And end with a simpler matrix:

That is, we start with a general matrix: And end with a simpler matrix: DIAGON ALIZATION OF THE STR ESS TEN SOR INTRO DUCTIO N By th us of Cauchy s thorm w ar abl to rduc th numbr of strss componnts in th strss tnsor to only nin valus. An additional simplification of th strss

More information

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation. Lur 7 Fourir Transforms and th Wav Euation Ovrviw and Motivation: W first discuss a fw faturs of th Fourir transform (FT), and thn w solv th initial-valu problm for th wav uation using th Fourir transform

More information

1997 AP Calculus AB: Section I, Part A

1997 AP Calculus AB: Section I, Part A 997 AP Calculus AB: Sction I, Part A 50 Minuts No Calculator Not: Unlss othrwis spcifid, th domain of a function f is assumd to b th st of all ral numbrs x for which f (x) is a ral numbr.. (4x 6 x) dx=

More information

On spanning trees and cycles of multicolored point sets with few intersections

On spanning trees and cycles of multicolored point sets with few intersections On spanning trs and cycls of multicolord point sts with fw intrsctions M. Kano, C. Mrino, and J. Urrutia April, 00 Abstract Lt P 1,..., P k b a collction of disjoint point sts in R in gnral position. W

More information

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA NE APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA Mirca I CÎRNU Ph Dp o Mathmatics III Faculty o Applid Scincs Univrsity Polithnica o Bucharst Cirnumirca @yahoocom Abstract In a rcnt papr [] 5 th indinit intgrals

More information

10. The Discrete-Time Fourier Transform (DTFT)

10. The Discrete-Time Fourier Transform (DTFT) Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w

More information

A Propagating Wave Packet Group Velocity Dispersion

A Propagating Wave Packet Group Velocity Dispersion Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to

More information

arxiv: v1 [math.nt] 13 Sep 2016

arxiv: v1 [math.nt] 13 Sep 2016 EXPLICIT EVALUATION OF DOUBLE GAUSS SUMS ŞABAN ALACA AND GREG DOYLE arxiv:6090399v [mathnt] 3 S 06 Abstract W rsnt an xlicit valuation of th doubl Gauss sum G(a,b,c;S; n := n x, πis(ax +bxy+cy / n, whr

More information

1 Isoparametric Concept

1 Isoparametric Concept UNIVERSITY OF CALIFORNIA BERKELEY Dpartmnt of Civil Enginring Spring 06 Structural Enginring, Mchanics and Matrials Profssor: S. Govindj Nots on D isoparamtric lmnts Isoparamtric Concpt Th isoparamtric

More information

u 3 = u 3 (x 1, x 2, x 3 )

u 3 = u 3 (x 1, x 2, x 3 ) Lctur 23: Curvilinar Coordinats (RHB 8.0 It is oftn convnint to work with variabls othr than th Cartsian coordinats x i ( = x, y, z. For xampl in Lctur 5 w mt sphrical polar and cylindrical polar coordinats.

More information

1997 AP Calculus AB: Section I, Part A

1997 AP Calculus AB: Section I, Part A 997 AP Calculus AB: Sction I, Part A 50 Minuts No Calculator Not: Unlss othrwis spcifid, th domain of a function f is assumd to b th st of all ral numbrs for which f () is a ral numbr.. (4 6 ) d= 4 6 6

More information

Square of Hamilton cycle in a random graph

Square of Hamilton cycle in a random graph Squar of Hamilton cycl in a random graph Andrzj Dudk Alan Friz Jun 28, 2016 Abstract W show that p = n is a sharp thrshold for th random graph G n,p to contain th squar of a Hamilton cycl. This improvs

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 07 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat

More information

Mor Tutorial at www.dumblittldoctor.com Work th problms without a calculator, but us a calculator to chck rsults. And try diffrntiating your answrs in part III as a usful chck. I. Applications of Intgration

More information

Construction of asymmetric orthogonal arrays of strength three via a replacement method

Construction of asymmetric orthogonal arrays of strength three via a replacement method isid/ms/26/2 Fbruary, 26 http://www.isid.ac.in/ statmath/indx.php?modul=prprint Construction of asymmtric orthogonal arrays of strngth thr via a rplacmnt mthod Tian-fang Zhang, Qiaoling Dng and Alok Dy

More information

Optimizing Product Launches in the Presence of Strategic Consumers Appendix

Optimizing Product Launches in the Presence of Strategic Consumers Appendix Optimizing Product Launchs in th Prsnc of Stratgic Consumrs Appndix Ilan Lobl Jigar Patl Gustavo Vulcano Jiawi Zhang Lonard N. Strn School of Businss, Nw York Univrsity, 44 Wst Fourth St., Nw York, NY

More information

Bifurcation Theory. , a stationary point, depends on the value of α. At certain values

Bifurcation Theory. , a stationary point, depends on the value of α. At certain values Dnamic Macroconomic Thor Prof. Thomas Lux Bifurcation Thor Bifurcation: qualitativ chang in th natur of th solution occurs if a paramtr passs through a critical point bifurcation or branch valu. Local

More information

Brief Introduction to Statistical Mechanics

Brief Introduction to Statistical Mechanics Brif Introduction to Statistical Mchanics. Purpos: Ths nots ar intndd to provid a vry quick introduction to Statistical Mchanics. Th fild is of cours far mor vast than could b containd in ths fw pags.

More information

Estimation of apparent fraction defective: A mathematical approach

Estimation of apparent fraction defective: A mathematical approach Availabl onlin at www.plagiarsarchlibrary.com Plagia Rsarch Library Advancs in Applid Scinc Rsarch, 011, (): 84-89 ISSN: 0976-8610 CODEN (USA): AASRFC Estimation of apparnt fraction dfctiv: A mathmatical

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 0 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat th

More information

(Upside-Down o Direct Rotation) β - Numbers

(Upside-Down o Direct Rotation) β - Numbers Amrican Journal of Mathmatics and Statistics 014, 4(): 58-64 DOI: 10593/jajms0140400 (Upsid-Down o Dirct Rotation) β - Numbrs Ammar Sddiq Mahmood 1, Shukriyah Sabir Ali,* 1 Dpartmnt of Mathmatics, Collg

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim and n a positiv intgr, lt ν p (n dnot th xponnt of p in n, and u p (n n/p νp(n th unit part of n. If α

More information

Quasi-Classical States of the Simple Harmonic Oscillator

Quasi-Classical States of the Simple Harmonic Oscillator Quasi-Classical Stats of th Simpl Harmonic Oscillator (Draft Vrsion) Introduction: Why Look for Eignstats of th Annihilation Oprator? Excpt for th ground stat, th corrspondnc btwn th quantum nrgy ignstats

More information

ME 321 Kinematics and Dynamics of Machines S. Lambert Winter 2002

ME 321 Kinematics and Dynamics of Machines S. Lambert Winter 2002 3.4 Forc Analysis of Linkas An undrstandin of forc analysis of linkas is rquird to: Dtrmin th raction forcs on pins, tc. as a consqunc of a spcifid motion (don t undrstimat th sinificanc of dynamic or

More information

Homotopy perturbation technique

Homotopy perturbation technique Comput. Mthods Appl. Mch. Engrg. 178 (1999) 257±262 www.lsvir.com/locat/cma Homotopy prturbation tchniqu Ji-Huan H 1 Shanghai Univrsity, Shanghai Institut of Applid Mathmatics and Mchanics, Shanghai 272,

More information

Function Spaces. a x 3. (Letting x = 1 =)) a(0) + b + c (1) = 0. Row reducing the matrix. b 1. e 4 3. e 9. >: (x = 1 =)) a(0) + b + c (1) = 0

Function Spaces. a x 3. (Letting x = 1 =)) a(0) + b + c (1) = 0. Row reducing the matrix. b 1. e 4 3. e 9. >: (x = 1 =)) a(0) + b + c (1) = 0 unction Spacs Prrquisit: Sction 4.7, Coordinatization n this sction, w apply th tchniqus of Chaptr 4 to vctor spacs whos lmnts ar functions. Th vctor spacs P n and P ar familiar xampls of such spacs. Othr

More information

A. Limits and Horizontal Asymptotes ( ) f x f x. f x. x "±# ( ).

A. Limits and Horizontal Asymptotes ( ) f x f x. f x. x ±# ( ). A. Limits and Horizontal Asymptots What you ar finding: You can b askd to find lim x "a H.A.) problm is asking you find lim x "# and lim x "$#. or lim x "±#. Typically, a horizontal asymptot algbraically,

More information

The Frequency Response of a Quarter-Wave Matching Network

The Frequency Response of a Quarter-Wave Matching Network 4/1/29 Th Frquncy Rsons o a Quartr 1/9 Th Frquncy Rsons o a Quartr-Wav Matchg Ntwork Q: You hav onc aga rovidd us with conusg and rhas uslss ormation. Th quartr-wav matchg ntwork has an xact SFG o: a Τ

More information

Heat/Di usion Equation. 2 = 0 k constant w(x; 0) = '(x) initial condition. ( w2 2 ) t (kww x ) x + k(w x ) 2 dx. (w x ) 2 dx 0.

Heat/Di usion Equation.  2 = 0 k constant w(x; 0) = '(x) initial condition. ( w2 2 ) t (kww x ) x + k(w x ) 2 dx. (w x ) 2 dx 0. Hat/Di usion Equation @w @t k @ w @x k constant w(x; ) '(x) initial condition w(; t) w(l; t) boundary conditions Enrgy stimat: So w(w t kw xx ) ( w ) t (kww x ) x + k(w x ) or and thrfor E(t) R l Z l Z

More information

#A27 INTEGERS 12 (2012) SUM-PRODUCTS ESTIMATES WITH SEVERAL SETS AND APPLICATIONS

#A27 INTEGERS 12 (2012) SUM-PRODUCTS ESTIMATES WITH SEVERAL SETS AND APPLICATIONS #A27 INTEGERS 12 (2012) SUM-PRODUCTS ESTIMATES WITH SEVERAL SETS AND APPLICATIONS Antal Balog Alfréd Rényi Institut of Mathmatics, Hungarian Acadmy of Scincs, Budast, Hungary balog@rnyihu Kvin A Broughan

More information

The Equitable Dominating Graph

The Equitable Dominating Graph Intrnational Journal of Enginring Rsarch and Tchnology. ISSN 0974-3154 Volum 8, Numbr 1 (015), pp. 35-4 Intrnational Rsarch Publication Hous http://www.irphous.com Th Equitabl Dominating Graph P.N. Vinay

More information

Inference Methods for Stochastic Volatility Models

Inference Methods for Stochastic Volatility Models Intrnational Mathmatical Forum, Vol 8, 03, no 8, 369-375 Infrnc Mthods for Stochastic Volatility Modls Maddalna Cavicchioli Cá Foscari Univrsity of Vnic Advancd School of Economics Cannargio 3, Vnic, Italy

More information

arxiv: v1 [cs.cg] 11 Dec 2013

arxiv: v1 [cs.cg] 11 Dec 2013 A Siml Sw Lin Algorithm for Counting Triangulations and Psudo-triangulations Victor Alvarz Karl Bringmann Saurabh Ray arxiv:1312.3188v1 [cs.cg] 11 Dc 2013 Dcmbr 12, 2013 Abstract Lt P R 2 b a st of n oints.

More information

Approximation and Inapproximation for The Influence Maximization Problem in Social Networks under Deterministic Linear Threshold Model

Approximation and Inapproximation for The Influence Maximization Problem in Social Networks under Deterministic Linear Threshold Model 20 3st Intrnational Confrnc on Distributd Computing Systms Workshops Approximation and Inapproximation for Th Influnc Maximization Problm in Social Ntworks undr Dtrministic Linar Thrshold Modl Zaixin Lu,

More information

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK Data Assimilation 1 Alan O Nill National Cntr for Earth Obsrvation UK Plan Motivation & basic idas Univariat (scalar) data assimilation Multivariat (vctor) data assimilation 3d-Variational Mthod (& optimal

More information

Some remarks on Kurepa s left factorial

Some remarks on Kurepa s left factorial Som rmarks on Kurpa s lft factorial arxiv:math/0410477v1 [math.nt] 21 Oct 2004 Brnd C. Kllnr Abstract W stablish a connction btwn th subfactorial function S(n) and th lft factorial function of Kurpa K(n).

More information

Problem Set 6 Solutions

Problem Set 6 Solutions 6.04/18.06J Mathmatics for Computr Scinc March 15, 005 Srini Dvadas and Eric Lhman Problm St 6 Solutions Du: Monday, March 8 at 9 PM in Room 3-044 Problm 1. Sammy th Shark is a financial srvic providr

More information

1.2 Faraday s law A changing magnetic field induces an electric field. Their relation is given by:

1.2 Faraday s law A changing magnetic field induces an electric field. Their relation is given by: Elctromagntic Induction. Lorntz forc on moving charg Point charg moving at vlocity v, F qv B () For a sction of lctric currnt I in a thin wir dl is Idl, th forc is df Idl B () Elctromotiv forc f s any

More information

Application of Vague Soft Sets in students evaluation

Application of Vague Soft Sets in students evaluation Availabl onlin at www.plagiarsarchlibrary.com Advancs in Applid Scinc Rsarch, 0, (6):48-43 ISSN: 0976-860 CODEN (USA): AASRFC Application of Vagu Soft Sts in studnts valuation B. Chtia*and P. K. Das Dpartmnt

More information

Estimation over Communication Networks: Performance Bounds and Achievability Results

Estimation over Communication Networks: Performance Bounds and Achievability Results Estimation ovr Communication Ntworks: Prformanc Bounds and Achivability Rsults A. F. Dana, V. Guta, J. P. Hsanha, B. Hassibi R. M. Murray Abstract This ar considrs th roblm of stimation ovr communication

More information

First derivative analysis

First derivative analysis Robrto s Nots on Dirntial Calculus Chaptr 8: Graphical analysis Sction First drivativ analysis What you nd to know alrady: How to us drivativs to idntiy th critical valus o a unction and its trm points

More information

1973 AP Calculus AB: Section I

1973 AP Calculus AB: Section I 97 AP Calculus AB: Sction I 9 Minuts No Calculator Not: In this amination, ln dnots th natural logarithm of (that is, logarithm to th bas ).. ( ) d= + C 6 + C + C + C + C. If f ( ) = + + + and ( ), g=

More information

The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012

The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012 Th van dr Waals intraction D. E. Sopr 2 Univrsity of Orgon 20 pril 202 Th van dr Waals intraction is discussd in Chaptr 5 of J. J. Sakurai, Modrn Quantum Mchanics. Hr I tak a look at it in a littl mor

More information

What are those βs anyway? Understanding Design Matrix & Odds ratios

What are those βs anyway? Understanding Design Matrix & Odds ratios Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.

More information

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim. MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function

More information

EXST Regression Techniques Page 1

EXST Regression Techniques Page 1 EXST704 - Rgrssion Tchniqus Pag 1 Masurmnt rrors in X W hav assumd that all variation is in Y. Masurmnt rror in this variabl will not ffct th rsults, as long as thy ar uncorrlatd and unbiasd, sinc thy

More information

Finding low cost TSP and 2-matching solutions using certain half integer subtour vertices

Finding low cost TSP and 2-matching solutions using certain half integer subtour vertices Finding low cost TSP and 2-matching solutions using crtain half intgr subtour vrtics Sylvia Boyd and Robrt Carr Novmbr 996 Introduction Givn th complt graph K n = (V, E) on n nods with dg costs c R E,

More information

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018 Propositional Logic Combinatorial Problm Solving (CPS) Albrt Olivras Enric Rodríguz-Carbonll May 17, 2018 Ovrviw of th sssion Dfinition of Propositional Logic Gnral Concpts in Logic Rduction to SAT CNFs

More information

MCB137: Physical Biology of the Cell Spring 2017 Homework 6: Ligand binding and the MWC model of allostery (Due 3/23/17)

MCB137: Physical Biology of the Cell Spring 2017 Homework 6: Ligand binding and the MWC model of allostery (Due 3/23/17) MCB37: Physical Biology of th Cll Spring 207 Homwork 6: Ligand binding and th MWC modl of allostry (Du 3/23/7) Hrnan G. Garcia March 2, 207 Simpl rprssion In class, w drivd a mathmatical modl of how simpl

More information

Stochastic Submodular Maximization

Stochastic Submodular Maximization Stochastic Submodular Maximization Arash Asadpour, Hamid Nazrzadh, and Amin Sabri Stanford Univrsity, Stanford, CA. {asadpour,hamidnz,sabri}@stanford.du Abstract. W study stochastic submodular maximization

More information

AS 5850 Finite Element Analysis

AS 5850 Finite Element Analysis AS 5850 Finit Elmnt Analysis Two-Dimnsional Linar Elasticity Instructor Prof. IIT Madras Equations of Plan Elasticity - 1 displacmnt fild strain- displacmnt rlations (infinitsimal strain) in matrix form

More information

3 Finite Element Parametric Geometry

3 Finite Element Parametric Geometry 3 Finit Elmnt Paramtric Gomtry 3. Introduction Th intgral of a matrix is th matrix containing th intgral of ach and vry on of its original componnts. Practical finit lmnt analysis rquirs intgrating matrics,

More information

Altruism, Selfishness, and Spite in Traffic Routing

Altruism, Selfishness, and Spite in Traffic Routing Altruism, Slfishnss, and Spit in Traffic Routing Po-An Chn Univrsity of Southrn California poanchn@usc.du David Kmp Univrsity of Southrn California dkmp@usc.du ABSTRACT In this papr, w study th pric of

More information

Division of Mechanics Lund University MULTIBODY DYNAMICS. Examination Name (write in block letters):.

Division of Mechanics Lund University MULTIBODY DYNAMICS. Examination Name (write in block letters):. Division of Mchanics Lund Univrsity MULTIBODY DYNMICS Examination 7033 Nam (writ in block lttrs):. Id.-numbr: Writtn xamination with fiv tasks. Plas chck that all tasks ar includd. clan copy of th solutions

More information

4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon.

4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon. PART I TRUE/FALSE/UNCERTAIN (5 points ach) 1. Lik xpansionary montary policy, xpansionary fiscal policy rturns output in th mdium run to its natural lvl, and incrass prics. Thrfor, fiscal policy is also

More information

Deift/Zhou Steepest descent, Part I

Deift/Zhou Steepest descent, Part I Lctur 9 Dift/Zhou Stpst dscnt, Part I W now focus on th cas of orthogonal polynomials for th wight w(x) = NV (x), V (x) = t x2 2 + x4 4. Sinc th wight dpnds on th paramtr N N w will writ π n,n, a n,n,

More information

ABEL TYPE THEOREMS FOR THE WAVELET TRANSFORM THROUGH THE QUASIASYMPTOTIC BOUNDEDNESS

ABEL TYPE THEOREMS FOR THE WAVELET TRANSFORM THROUGH THE QUASIASYMPTOTIC BOUNDEDNESS Novi Sad J. Math. Vol. 45, No. 1, 2015, 201-206 ABEL TYPE THEOREMS FOR THE WAVELET TRANSFORM THROUGH THE QUASIASYMPTOTIC BOUNDEDNESS Mirjana Vuković 1 and Ivana Zubac 2 Ddicatd to Acadmician Bogoljub Stanković

More information