A Game-theoretical Approach for Job Shop Scheduling Considering Energy Cost in Service Oriented Manufacturing

Size: px
Start display at page:

Download "A Game-theoretical Approach for Job Shop Scheduling Considering Energy Cost in Service Oriented Manufacturing"

Transcription

1 06 Inernaonal Conferene on Appled Mehans, Mehanal and Maerals Engneerng (AMMME 06) ISBN: A Game-heoreal Approah for Job Shop Shedulng Consderng Energy Cos n Serve Orened Manufaurng Chang-le TIAN, Guang-hu ZHOU * and Feng-an CHANG Shool of Mehanal Engneerng, X an Jaoong Unversy, X an 70049, Chna *Correspondng auhor Keywords: Serve-orened manufaurng, Energy os, Job shop shedulng, Nash equlbrum, Non-ooperave game. Absra. In serve-orened manufaurng mode, a large amoun of enerprses open her workshops o provde manufaurng serve, and produon ousourng and usomer sasfaon are wo rual manners o make profs. In serve orened manufaurng workshops, jobs ome from dfferen usomers. Compeve relaonshp among usomers should be nevably aken no aoun owng o he openness haraers of workshops and neress maxmzaon pursu of eah usomer. Moreover, beause of nreasng energy pre, arbon ax poly, arbon label poly, mos of usomers and manufaurng ompanes are urgenly eager o redue energy onsumpon o save os. Based on above-menoned requremens, n hs paper, a non-ooperave game model for job shop shedulng based on ndvdual profs maxmzaon n serve orened manufaurng envronmen s gven. I akes usomer s os as opmal objeves n whh energy os of manufaurng proess and ransporaon proess are onsdered. Fnally, one ase s arred ou o valdae he raonaly of he proposed model. Inroduon Serve-orened manufaurng mode has emerged as a novel and promsng manufaurng paradgm, whh s beng wdely appled n he global manufaurng ndusry. In serve-orened manufaurng mode, produon ousourng and usomer sasfaon are wo rual manners o make profs and realze value nremen []. Conreely speakng, manufaurng frms are wllng o open her workshops o provde manufaurng serve o make exra money. I s obvous ha hgher sasfaon from eah usom s soure for hem o wn he profs. In radonal Make o Sok produon mode, he manufaurers, wh he purpose of opmzng her own global objeves (makespan, os and so on), are poenally nlned o gnore he neress of paral usomers. However, as serve-orened manufaurng mode sprngs up, produon mode has been ransformed o Make o Order. In hs mode, eah usomer who plans o ousoure her jobs o serve-orened manufaurng enerprses furher hghlghs her own opmal profs (he probable lowes os, he possble earles delvery dae). In order o aommodae o hs new produon paern and aheve hgher sasfaon from eah usom, manufaurers are oblged o pay muh more aenon o maxmze profs of jobs of eah usomer. These jobs are proessed n hs new open serve-orened manufaurng job shop wh dsrbued manufaurng resoures or serves. However, beause of he openness and fneness of manufaurng resoures, s neessary for manufaurers o make eah len onend for manufaurng resoures so ha he greaes benef of ndvdual ould be aheved. Moreover, wh dramaally hange of global lmae, energy onsumpon of manufaurng draw publ onern. Aordng o ehnology a of European Unon abou radng energy nensve produs, for hna, s anpaed ha abou 80% produs whh exeed a gven energy onsumpon would be kep ou of EU []. Thus, s mperave for manufaurers and eah len o hghlgh he energy onsumpon faor relaed o her neress. Shop shedulng no only ould qukly and reasonably alloae he lmed manufaurng resoures so as o mprove mahnng effeny, qualy and so on, bu also ould opmze he requremens of usomers.

2 Therefore, n shop shedulng wh lmed shop resoures, how o maxmze eah usomer s ore neress onsderng energy onsumpon based on her ompeve relaonshp would be a new fous. In order o response o lmae hange, a grea many of leraures akng no energy and arbon emssons aoun abou job shop shedulng problems. He e al. [3] proposed an energy-responsve opmzaon mehod o opmze mahnng operaons and he dle energy onsumpon of mahne ools. Zhang e al. presened a model of low-arbon shedulng of he flexble job shop, esablshed a quanave arbon fooprn model of mul-job proessng, and pu forward hree arbon effeny ndaors. Song e al. [5] nrodued energy onsumpon faors no flexble job-shop shedulng problem wh manenane aves, amng a mnmzng maxmum ompleon me, oal produon energy oss and oal energy oss of manenane smulaneously. Sok e al. [6] esablshed a mul-objeve shop floor shedulng usng monored energy daa desrbed by energy-plannng daabase nludng relaed mahng operaons, proessng mahnes, and proessng parameers. All n all, an be learly seen ha hough many of sholars dsussed job shedulng ssue allowng for he envronmenally frendly faors, few sholars ondued sudy of shop shedulng n onsderng of energy onsumpon based on ompeve relaonshp among jobs. In vew of new haraerss of job shop shedulng, a non-ooperave game model for job shop shedulng s gven. Compared wh radonal shedulng model, he proposed novel shedulng model drven by he demands of lens, onenraes on he ompeve relaonshps o aan maxmum of profs of eah usomer. The goal of hs model s he oal os nvolvng energy os n manufaurng proess and ransporaon proess, manufaurng os, ransporaon os and penaly os under he onsran of due-dae. To ge he opmal shedulng resuls, a gene algorhm s adoped o fnd an approxmae Nash equlbrum (NE) pon of he model. Model Desrpon Energy Consumpon Model In a serve orened manufaurng workshop, here are N jobs need o be proessed and eah job has n sequened operaons. The produon of an operaon nvolves many manufaurng aves. These manufaurng aves, suh as sar and sop proess, ung proess, ools hangng proess and ransporaon proess, are losely relaed o he energy onsumpon. However, n hese proesses, he proess of sar and sop and he proess of ools hange susan a shor perod of me whh s dfful o measure hese mes. So, an average negraed power s used o alulae he energy onsumpon whn he omprehensve proess me. The manufaurng energy onsumpon CE of operaon j of job s shown n Eq. () j CE = P () j j jk Obvously, he manufaurng energy onsumpon CE of job ould be expressed n Eq. () CE n = CEj () j= The ransporaon proess energy onsumpon CE of job s alulaed wh Eq. (3) n = v j, j j= CE P p (3) Where jk denoes he proessng me of operaon j of job on mahne k, P j denoes he average negraed power of operaon j of job on mahne k, P v denoes he power of vehles,

3 p j, j denoes ransporaon me beween mahne j and j. Therefore, he energy onsumpon of job s he sum of energy onsumpon of manufaurng proess and ransporaon proess, as shown n Eq. (4) CE = CE + CE (4) Non-ooperave Game Model for Job Shop Shedulng The whole framework of he model s shown n Fgure, here are N usomers and eah usomer has one Job whh nludes a sequene of operaons. These Jobs need o proess n he workshop G, whh nludes r dsrbued mahnes and g vehles used o ranspor job. Eah usomer hoose s sraegy s by dedng mahne for eah operaon so ha s own payoff aheve he bes. The payoff of usomer affeed no only by s own sraegy bu also oher N- usomers seleable sraeges beause of varous proess sequenes. In hs model, he players refer o he jobs submed by relaed usomer, he sraeges of eah job refer o he seleable mahnes relaed o he operaons of hs job, and he payoff of eah job refers o oal os. Job Job Job N Job Job Job N Sraeges profes Job Job Job N Nash profes Payoff Payoff Payoff N Fgure. The framework of he model. The non-ooperave model s made up of players, sraeges, and payoffs. The proposed model an be desrbed as he form G ( W, H, Y).Spefally n hs model, W represens players, namely N usomers. H represens sraegy adoped by eah player ha s he seleable mahnes for eah usomer, ha s X, X = X X X n, X denoes sraegy se of J. Y represens he se of payoffs funon for players. For hs model, eah player has s pay-off funon, ha s: Manufaurng os pay-off funon: n n a d b d U ( x) = = rk jk + r max{0,( )} + r max{0,( )} + p p k, k + j= k= (5) Energy os pay-off funon: n n ( ) = j jk r + v j, j r j= j= (6) U x P q P p q The oal payoff funon s: U = U + U (7) x = x,, xn x X and subje o: Where ( )

4 d ( x) = (8) s ( x ) + ( x ) = ( x ) (9) jk jk jk p, =,, N. j =, n. k =,, M (0) s jk ( j+ )(k + ) k, k + s ( x ) ( x ),, q =, N. j =, n, l =, n. k =, m () Where jk qlk q mahne k, s jk denoes he sar me of O j on mahne k, jk denoes he ompleon me of O j on denoes he fnsh me of job, d denoes he due dae of job, r k denoes he proess pre on mahne k, r denoes he un pre of ask due o pospone delvery me, b un pre of ask due o nvenory os aused by delvery me n advane. r elery, p denoes he pre of ransporaon of job. a r he q denoes he pre of Equaon (8) ensures he onsran of delvery of J n serve orened manufaurng envronmen. Formula (9), (0) ensure he onsran ha one operaon mus be proessed only on one mahne a a me. And nequaly () guaranees he onsran ha one mahne mus proess only one operaon a a me. In a word, eah player wans o mnmze s payoff-funon value and nrease opponen s payoff-funon value. s he ore of he model o balane he neress of eah player o oban opmal shedulng resul. For hs non-ooperave game model for job-shop shedulng, n he Nash Equlbrum pon, he opmal shedulng resul sasfes he followng nequaly (). Therefore, he problem seekng he opmal shedulng resul wll be ransformed no he queson, namely alulang he Nash equlbrum pon of he model. U ( x, x, x, x, x +,, x ) U ( x, x, x, x, x +,, xn ) N x X, =,,N () Smulaon Case Frs, a smulaon ase s desgned. The nal relaed daa s gven n Table. In erms of eah ell n he Table, onans hree groups of daa, and a group of daa s enrled by a par of quadrae parenheses. The upper group daa means he seleable mahne ools of operaon O, he seond se of daa means he proessng me orrespondng o he seleable mahne, and he hrd se of daa means he proessng power orrespondng o he seleable mahne. Furhermore, ransporaon me beween wo mahnes s shown n Table. The number,, 8 lsed n he frs olumn and n he frs row respevely represens he ID of eah mahne. Eah elemen n Table denoes ransporaon me alulaed by he rao of he ransporaon dsane and ransporaon speed beween mahnes. In addon, he proessng pre of eah mahne s shown n Table 3. In addon, Table 4 gves he dealed parameers of eah job, nludng he delvery dae, ardness penaly, earlness penaly, and pre of ransporaon. j

5 Table. Soure daa of he smulaon ase. J J J J 3 J 4 J 5 J 6 J 7 J 8 operaons [,5] [3,] [3,5] [4,] [,6] [3,6] [3,7] [7, 6] [,8] [,6] [] [5,8] [7,7] [,5] [,8] [9,8] [5,3] [3,] [4,6] [8,5] [,6] [4,6] [8,6] [3,5] [,7] [8,7] [5,3] [,3] [5,4] [,5] [7,5] [4,] [8,7] [,7] [7,7] [4,7] [,8] [7,5] [] [3] [4,7] [9,5] [7,7] [5] [6] [3] [8] [,] [3,7] [3,] [,7] [7,5] [,5] [5,8] [,3,7] [5,8,7] [5,4,3] [,,4] [8,7,6] [5,3,4] [8,7] Table. The ransporaon me beween wo mahnes. [,3,8] [5,6,6] [,3,3] [3,6] [,7] [3,5] [,8] [,] [,7 [9,8] [,8] [8,6] [,6] [4,] [5,8] [6] [3] Mahne Table 3. The proessng pre of eah mahne per hour. Mahne Pre(RMB/hour) Table 4. The dealed parameers of eah job. J J J3 J 4 J5 J6 J7 J8 Job Delvery dae(/h) Tardness penaly (RMB/h) Earlness penaly (RMB/h) Pre of ransporaon (RMB/h) 3 3

6 J Table 5. The payoff value of jobs n s and he equlbrum generaon. s generaon / RMB payoff The equlbrum generaon / RMB J J 39 4 J J J J J J Compared wh he s generaon, os of eah job noably derease n Equlbrum generaon and eah usomer s wllng o hange her sraegy, so an approxmae NE s found and aepable. Summary In hs paper, foremos, he haraerss of shop shedulng n serve-orened manufaurng envronmen s elaboraed and s dsnon wh radonal shedulng s denfed. In addon, he energy onsumpon onsdered n he arle nludes wo ypes, namely he energy onsumpon of ung proess and he energy onsumpon of ransporaon proess among mahnes. More mporanly, based on hose haraerss, a novel non-ooperave game model for job shop shedulng n serve-orened manufaurng envronmen s pu forward, whh akes he faors of energy os no aouns. Fnally, a ase s appled o demonsrae he raonaly and feasbly of he proposed model. Insead of fousng on overall energy onsumpon, from he perspeve of usomers, redung os s possble. The nex sep for hs researh feld wll pay more aenon o he mehod n how o alloae he dle energy onsumpon o usomers n serve-orened manufaurng envronmen. Aknowledgemen Ths researh s suppored by he Naonal Naural Sene Foundaon of Chna (gran no ). Referenes [] Lang, P., Sun, Y. & L, W.,Year.Serve-orened manufaurng nformaon sysem: Conep, arheure and fous of fuure researhed. Inernaonal Conferene on Serve Sysems and Serve Managemen. [] hp://xh.xhby.ne/mp/hml/008-08/8/onen_8436.hm. [3] He, Y., L, Y., Wu, T. & Suherland, J.W.An energy-responsve opmzaon mehod for mahne ool seleon and operaon sequene n flexble mahnng job shops,journal of Cleaner Produon, 87 (05), Zhang, C., Gu, P. & Jang, P. Low-arbon shedulng and esmang for a flexble job shop based on arbon fooprn and arbon effeny of mul-job proessng, Proeedngs of he Insuon of Mehanal Engneers Par B Journal of Engneerng Manufaure, 9 (04),

7 [5] Song, W.J., Zhang, C.Y., Ln, W.W. & Shao, X.Y.Flexble job-shop shedulng problem wh manenane aves onsderng energy onsumpon,appled Mehans & Maerals,5 (04), [6] Sok, T. & Selger, G.Mul-objeve shop floor shedulng usng monored energy daa, Proeda CIRP, 6 (05), Zhou, G., Jang, P. & Huang, G.Q.A game-heory approah for job shedulng n neworked manufaurng,the Inernaonal Journal of Advaned Manufaurng Tehnology, 4 (009),

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION MACROECONOMIC THEORY T. J. KEHOE ECON 85 FALL 7 ANSWERS TO MIDTERM EXAMINATION. (a) Wh an Arrow-Debreu markes sruure fuures markes for goods are open n perod. Consumers rade fuures onras among hemselves.

More information

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions.

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions. Problem Se 3 EC450A Fall 06 Problem There are wo ypes of ndvduals, =, wh dfferen ables w. Le be ype s onsumpon, l be hs hours worked and nome y = w l. Uly s nreasng n onsumpon and dereasng n hours worked.

More information

Lecture Notes 4: Consumption 1

Lecture Notes 4: Consumption 1 Leure Noes 4: Consumpon Zhwe Xu (xuzhwe@sju.edu.n) hs noe dsusses households onsumpon hoe. In he nex leure, we wll dsuss rm s nvesmen deson. I s safe o say ha any propagaon mehansm of maroeonom model s

More information

Computational results on new staff scheduling benchmark instances

Computational results on new staff scheduling benchmark instances TECHNICAL REPORT Compuaonal resuls on new saff shedulng enhmark nsanes Tm Curos Rong Qu ASAP Researh Group Shool of Compuer Sene Unersy of Nongham NG8 1BB Nongham UK Frs pulshed onlne: 19-Sep-2014 las

More information

Pendulum Dynamics. = Ft tangential direction (2) radial direction (1)

Pendulum Dynamics. = Ft tangential direction (2) radial direction (1) Pendulum Dynams Consder a smple pendulum wh a massless arm of lengh L and a pon mass, m, a he end of he arm. Assumng ha he fron n he sysem s proporonal o he negave of he angenal veloy, Newon s seond law

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

Optimal Replenishment Policy for Hi-tech Industry with Component Cost and Selling Price Reduction

Optimal Replenishment Policy for Hi-tech Industry with Component Cost and Selling Price Reduction Opmal Replenshmen Poly for H-eh Indusry wh Componen Cos and Sellng Pre Reduon P.C. Yang 1, H.M. Wee, J.Y. Shau, and Y.F. seng 1 1 Indusral Engneerng & Managemen Deparmen, S. John s Unversy, amsu, ape 5135

More information

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2 COMPUTE SCIENCE 49A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PATS, PAT.. a Dene he erm ll-ondoned problem. b Gve an eample o a polynomal ha has ll-ondoned zeros.. Consder evaluaon o anh, where e e anh. e e

More information

Citation 2006 Ieee Power Engineering Society General Meeting, Pes, 2006

Citation 2006 Ieee Power Engineering Society General Meeting, Pes, 2006 Tle Reave power plannng and s os alloaon for dsrbuon sysems wh dsrbued generaon Auhor(s) Chen, L; Zhong, J; Gan, D Caon 6 eee Power Engneerng Soey General Meeng, Pes, 6 ssued Dae 6 URL hp://hdl.handle.ne/7/459

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () we define the interaction representation by the unitary transformation () = () Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger

More information

)-interval valued fuzzy ideals in BF-algebras. Some properties of (, ) -interval valued fuzzy ideals in BF-algebra, where

)-interval valued fuzzy ideals in BF-algebras. Some properties of (, ) -interval valued fuzzy ideals in BF-algebra, where Inernaonal Journal of Engneerng Advaned Researh Tehnology (IJEART) ISSN: 454-990, Volume-, Issue-4, Oober 05 Some properes of (, )-nerval valued fuzzy deals n BF-algebras M. Idrees, A. Rehman, M. Zulfqar,

More information

Methods of Improving Constitutive Equations

Methods of Improving Constitutive Equations Mehods o mprovng Consuve Equaons Maxell Model e an mprove h ne me dervaves or ne sran measures. ³ ª º «e, d» ¼ e an also hange he bas equaon lnear modaons non-lnear modaons her Consuve Approahes Smple

More information

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b Inernaonal Indusral Informacs and Compuer Engneerng Conference (IIICEC 05) Arbue educon Algorhm Based on Dscernbly Marx wh Algebrac Mehod GAO Jng,a, Ma Hu, Han Zhdong,b Informaon School, Capal Unversy

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

Solution of Unit Commitment Problem Using Enhanced Genetic Algorithm

Solution of Unit Commitment Problem Using Enhanced Genetic Algorithm Soluon of Un Commmen roblem Usng Enhaned Gene Algorhm raeek K. Snghal, R. Naresh 2 Deparmen of Eleral Engneerng Naonal Insue of ehnology, Hamrpur Hmahal radesh, Inda-77005 snghalkpraeek@gmal.om, 2 rnareshnh@gmal.om

More information

Nurturing a New Low Carbon Sector under Uncertainty of Fuel Economy and Renewable Sources Development

Nurturing a New Low Carbon Sector under Uncertainty of Fuel Economy and Renewable Sources Development Nururng a New Low Carbon Seor under Unerany of Fuel Eonomy and Renewable Soures Developmen a Nmura a, Hrosh aamor b, Da Yamasa, Wang d, and Ryuh Yooyama e a Fauly of Eonoms, Hose Unversy b Waseda Unversy

More information

Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article Avalable onlne.jopr.om Journal o Chemal Pharmaeual Researh, 014, 6(5:44-48 Researh Arle ISS : 0975-7384 CODE(USA : JCPRC5 Perormane evaluaon or engneerng proje managemen o parle sarm opmzaon based on leas

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4 CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he

More information

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate Macroeconomics 2 Problem set 5. - Solutions Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K

More information

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits. ose ad Varably Homewor # (8), aswers Q: Power spera of some smple oses A Posso ose A Posso ose () s a sequee of dela-fuo pulses, eah ourrg depedely, a some rae r (More formally, s a sum of pulses of wdh

More information

Epistemic Game Theory: Online Appendix

Epistemic Game Theory: Online Appendix Epsemc Game Theory: Onlne Appendx Edde Dekel Lucano Pomao Marcano Snscalch July 18, 2014 Prelmnares Fx a fne ype srucure T I, S, T, β I and a probably µ S T. Le T µ I, S, T µ, βµ I be a ype srucure ha

More information

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong

More information

Regularization and Stabilization of the Rectangle Descriptor Decentralized Control Systems by Dynamic Compensator

Regularization and Stabilization of the Rectangle Descriptor Decentralized Control Systems by Dynamic Compensator www.sene.org/mas Modern Appled ene Vol. 5, o. 2; Aprl 2 Regularzaon and ablzaon of he Reangle Desrpor Deenralzed Conrol ysems by Dynam Compensaor Xume Tan Deparmen of Eleromehanal Engneerng, Heze Unversy

More information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class

More information

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,

More information

Robust and Accurate Cancer Classification with Gene Expression Profiling

Robust and Accurate Cancer Classification with Gene Expression Profiling Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem

More information

Lecture 11 SVM cont

Lecture 11 SVM cont Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc

More information

Chapter Lagrangian Interpolation

Chapter Lagrangian Interpolation Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and

More information

Solving the multi-period fixed cost transportation problem using LINGO solver

Solving the multi-period fixed cost transportation problem using LINGO solver Inernaonal Journal of Pure and Appled Mahemacs Volume 119 No. 12 2018, 2151-2157 ISSN: 1314-3395 (on-lne verson) url: hp://www.pam.eu Specal Issue pam.eu Solvng he mul-perod fxed cos ransporaon problem

More information

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5 TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres

More information

Robustness Experiments with Two Variance Components

Robustness Experiments with Two Variance Components Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference

More information

Linear Quadratic Regulator (LQR) - State Feedback Design

Linear Quadratic Regulator (LQR) - State Feedback Design Linear Quadrai Regulaor (LQR) - Sae Feedbak Design A sysem is expressed in sae variable form as x = Ax + Bu n m wih x( ) R, u( ) R and he iniial ondiion x() = x A he sabilizaion problem using sae variable

More information

Controller Design for Networked Control Systems in Multiple-packet Transmission with Random Delays

Controller Design for Networked Control Systems in Multiple-packet Transmission with Random Delays Appled Mehans and Materals Onlne: 03-0- ISSN: 66-748, Vols. 78-80, pp 60-604 do:0.408/www.sentf.net/amm.78-80.60 03 rans eh Publatons, Swtzerland H Controller Desgn for Networed Control Systems n Multple-paet

More information

Optimal environmental charges under imperfect compliance

Optimal environmental charges under imperfect compliance ISSN 1 746-7233, England, UK World Journal of Modellng and Smulaon Vol. 4 (28) No. 2, pp. 131-139 Opmal envronmenal charges under mperfec complance Dajn Lu 1, Ya Wang 2 Tazhou Insue of Scence and Technology,

More information

Electromagnetic waves in vacuum.

Electromagnetic waves in vacuum. leromagne waves n vauum. The dsovery of dsplaemen urrens enals a peular lass of soluons of Maxwell equaons: ravellng waves of eler and magne felds n vauum. In he absene of urrens and harges, he equaons

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

Sequential Unit Root Test

Sequential Unit Root Test Sequenal Un Roo es Naga, K, K Hom and Y Nshyama 3 Deparmen of Eonoms, Yokohama Naonal Unversy, Japan Deparmen of Engneerng, Kyoo Insue of ehnology, Japan 3 Insue of Eonom Researh, Kyoo Unversy, Japan Emal:

More information

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November

More information

Solution in semi infinite diffusion couples (error function analysis)

Solution in semi infinite diffusion couples (error function analysis) Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of

More information

The Maxwell equations as a Bäcklund transformation

The Maxwell equations as a Bäcklund transformation ADVANCED ELECTROMAGNETICS, VOL. 4, NO. 1, JULY 15 The Mawell equaons as a Bäklund ransformaon C. J. Papahrsou Deparmen of Physal Senes, Naval Aademy of Greee, Praeus, Greee papahrsou@snd.edu.gr Absra Bäklund

More information

Complex Dynamics Analysis for Cournot Game with Bounded Rationality in Power Market

Complex Dynamics Analysis for Cournot Game with Bounded Rationality in Power Market J. Elecromagnec Analyss & Applcaons 9 : 48- Publshed Onlne March 9 n ScRes (www.scrp.org/journal/jemaa Complex Dynamcs Analyss for Courno Game wh Bounded Raonaly n Power Marke Hongmng Yang Yongx Zhang

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

Optimal Adaptive Data Transmission over a Fading Channel with Deadline and Power Constraints

Optimal Adaptive Data Transmission over a Fading Channel with Deadline and Power Constraints Opmal Adapve Daa Transmsson over a Fadng Channel wh Deadlne and Power Consrans Muraza Zafer and yan Modano aboraory for Informaon and Deson Sysems Massahuses Insue of Tehnology Cambrdge, MA 239, USA emal:{muraza,modano}@m.edu

More information

The Dynamic Programming Models for Inventory Control System with Time-varying Demand

The Dynamic Programming Models for Inventory Control System with Time-varying Demand The Dynamc Programmng Models for Invenory Conrol Sysem wh Tme-varyng Demand Truong Hong Trnh (Correspondng auhor) The Unversy of Danang, Unversy of Economcs, Venam Tel: 84-236-352-5459 E-mal: rnh.h@due.edu.vn

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic Bezier Homotopy Function for Solving Exponential Equations Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.

More information

Development of a New Optimal Multilevel Thresholding Using Improved Particle Swarm Optimization Algorithm for Image Segmentation

Development of a New Optimal Multilevel Thresholding Using Improved Particle Swarm Optimization Algorithm for Image Segmentation Inernaonal Journal of Elerons Engneerng, (1), 010, pp. 63-67 Developmen of a New Opmal Mullevel Thresholdng Usng Improved Parle Swarm Opmzaon Algorhm for Image Segmenaon P.D. Sahya 1 & R. Kayalvzh 1 Deparmen

More information

Origin of the inertial mass (II): Vector gravitational theory

Origin of the inertial mass (II): Vector gravitational theory Orn of he neral mass (II): Veor ravaonal heory Weneslao Seura González e-mal: weneslaoseuraonzalez@yahoo.es Independen Researher Absra. We dedue he nduve fores of a veor ravaonal heory and we wll sudy

More information

A Deterministic Algorithm for Summarizing Asynchronous Streams over a Sliding Window

A Deterministic Algorithm for Summarizing Asynchronous Streams over a Sliding Window A Deermnsc Algorhm for Summarzng Asynchronous Sreams over a Sldng ndow Cosas Busch Rensselaer Polyechnc Insue Srkana Trhapura Iowa Sae Unversy Oulne of Talk Inroducon Algorhm Analyss Tme C Daa sream: 3

More information

2 Aggregate demand in partial equilibrium static framework

2 Aggregate demand in partial equilibrium static framework Unversy of Mnnesoa 8107 Macroeconomc Theory, Sprng 2009, Mn 1 Fabrzo Perr Lecure 1. Aggregaon 1 Inroducon Probably so far n he macro sequence you have deal drecly wh represenave consumers and represenave

More information

Optimal Buyer-Seller Inventory Models in Supply Chain

Optimal Buyer-Seller Inventory Models in Supply Chain Inernaonal Conference on Educaon echnology and Informaon Sysem (ICEIS 03 Opmal Buyer-Seller Invenory Models n Supply Chan Gaobo L Shandong Women s Unversy, Jnan, 50300,Chna emal: lgaobo_979@63.com Keywords:

More information

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. Ths documen s downloaded from DR-NTU, Nanyang Technologcal Unversy Lbrary, Sngapore. Tle A smplfed verb machng algorhm for word paron n vsual speech processng( Acceped verson ) Auhor(s) Foo, Say We; Yong,

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

Tools for Analysis of Accelerated Life and Degradation Test Data

Tools for Analysis of Accelerated Life and Degradation Test Data Acceleraed Sress Tesng and Relably Tools for Analyss of Acceleraed Lfe and Degradaon Tes Daa Presened by: Reuel Smh Unversy of Maryland College Park smhrc@umd.edu Sepember-5-6 Sepember 28-30 206, Pensacola

More information

Li An-Ping. Beijing , P.R.China

Li An-Ping. Beijing , P.R.China A New Type of Cpher: DICING_csb L An-Png Bejng 100085, P.R.Chna apl0001@sna.com Absrac: In hs paper, we wll propose a new ype of cpher named DICING_csb, whch s derved from our prevous sream cpher DICING.

More information

A NEW METHOD OF FMS SCHEDULING USING OPTIMIZATION AND SIMULATION

A NEW METHOD OF FMS SCHEDULING USING OPTIMIZATION AND SIMULATION A NEW METHD F FMS SCHEDULING USING PTIMIZATIN AND SIMULATIN Ezedeen Kodeekha Deparmen of Producon, Informacs, Managemen and Conrol Faculy of Mechancal Engneerng udapes Unversy of Technology and Econcs

More information

Math 128b Project. Jude Yuen

Math 128b Project. Jude Yuen Mah 8b Proec Jude Yuen . Inroducon Le { Z } be a sequence of observed ndependen vecor varables. If he elemens of Z have a on normal dsrbuon hen { Z } has a mean vecor Z and a varancecovarance marx z. Geomercally

More information

Method of Characteristics for Pure Advection By Gilberto E. Urroz, September 2004

Method of Characteristics for Pure Advection By Gilberto E. Urroz, September 2004 Mehod of Charaerss for Pre Adveon By Glbero E Urroz Sepember 004 Noe: The followng noes are based on lass noes for he lass COMPUTATIONAL HYDAULICS as agh by Dr Forres Holly n he Sprng Semeser 985 a he

More information

CS 268: Packet Scheduling

CS 268: Packet Scheduling Pace Schedulng Decde when and wha pace o send on oupu ln - Usually mplemened a oupu nerface CS 68: Pace Schedulng flow Ion Soca March 9, 004 Classfer flow flow n Buffer managemen Scheduler soca@cs.bereley.edu

More information

Output equals aggregate demand, an equilibrium condition Definition of aggregate demand Consumption function, c

Output equals aggregate demand, an equilibrium condition Definition of aggregate demand Consumption function, c Eonoms 435 enze D. Cnn Fall Soal Senes 748 Unversy of Wsonsn-adson Te IS-L odel Ts se of noes oulnes e IS-L model of naonal nome and neres rae deermnaon. Ts nvolves exendng e real sde of e eonomy (desred

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 Lecture 14: Quantum de Finetti Theorems II CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2

More information

Biol. 356 Lab 8. Mortality, Recruitment, and Migration Rates

Biol. 356 Lab 8. Mortality, Recruitment, and Migration Rates Biol. 356 Lab 8. Moraliy, Recruimen, and Migraion Raes (modified from Cox, 00, General Ecology Lab Manual, McGraw Hill) Las week we esimaed populaion size hrough several mehods. One assumpion of all hese

More information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes. umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal

More information

Decomposing exports growth differences across Spanish regions

Decomposing exports growth differences across Spanish regions Deomposng expors growh dfferenes aross Spansh regons Aser Mnondo* (Unversdad de Deuso) Franso Requena (Unversdad de Valena) Absra Why do expors grow faser n some regons han n ohers? The regonal leraure

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran

More information

The preemptive resource-constrained project scheduling problem subject to due dates and preemption penalties: An integer programming approach

The preemptive resource-constrained project scheduling problem subject to due dates and preemption penalties: An integer programming approach Journal of Indusral Engneerng 1 (008) 35-39 The preempve resource-consraned projec schedulng problem subjec o due daes and preempon penales An neger programmng approach B. Afshar Nadjaf Deparmen of Indusral

More information

WELFARE MEASUREMENT, INVOLUNTARY UNEMPLOYMENT, AND HETEROGENEITY

WELFARE MEASUREMENT, INVOLUNTARY UNEMPLOYMENT, AND HETEROGENEITY row_42 559..571 Revew of Inome and Wealh Seres 56, umber 3, Sepember 21 WELFARE EASUREET, IVOLUTARY UEPLOYET, AD HETEROGEEITY by Thomas Aronsson* Umeå Unversy Ths paper onerns welfare measuremen n an eonomy

More information

An introduction to Support Vector Machine

An introduction to Support Vector Machine An nroducon o Suppor Vecor Machne 報告者 : 黃立德 References: Smon Haykn, "Neural Neworks: a comprehensve foundaon, second edon, 999, Chaper 2,6 Nello Chrsann, John Shawe-Tayer, An Inroducon o Suppor Vecor Machnes,

More information

The Analysis of the Thickness-predictive Model Based on the SVM Xiu-ming Zhao1,a,Yan Wang2,band Zhimin Bi3,c

The Analysis of the Thickness-predictive Model Based on the SVM Xiu-ming Zhao1,a,Yan Wang2,band Zhimin Bi3,c h Naonal Conference on Elecrcal, Elecroncs and Compuer Engneerng (NCEECE The Analyss of he Thcknesspredcve Model Based on he SVM Xumng Zhao,a,Yan Wang,band Zhmn B,c School of Conrol Scence and Engneerng,

More information

TAX AND BENEFIT REFORMS

TAX AND BENEFIT REFORMS European Nework of Eonom Poly Researh Insues TAX AND BENEFIT REFORMS IN A MODEL OF LABOUR MARKET TRANSITIONS MICHAL MYCK AND HOWARD REED ENEPRI RESEARCH REPORT NO. 25 OCTOBER 2006 ENEPRI Researh Repors

More information

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β SARAJEVO JOURNAL OF MATHEMATICS Vol.3 (15) (2007), 137 143 SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β M. A. K. BAIG AND RAYEES AHMAD DAR Absrac. In hs paper, we propose

More information

Econ107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6)

Econ107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6) Econ7 Appled Economercs Topc 5: Specfcaon: Choosng Independen Varables (Sudenmund, Chaper 6 Specfcaon errors ha we wll deal wh: wrong ndependen varable; wrong funconal form. Ths lecure deals wh wrong ndependen

More information

Matlab and Python programming: how to get started

Matlab and Python programming: how to get started Malab and Pyhon programming: how o ge sared Equipping readers he skills o wrie programs o explore complex sysems and discover ineresing paerns from big daa is one of he main goals of his book. In his chaper,

More information

International Journal of Engineering & Technology IJET-IJENS Vol:13 No:02 104

International Journal of Engineering & Technology IJET-IJENS Vol:13 No:02 104 Inernaonal Journal of Engneerng & Tehnology IJET-IJENS Vol:1 No:0 10 Applaon of a Mehodology for Measurng Aerospae Pars by Ulrason Consderng he Measuremen Unerany hrough Analyal and Mone Carlo Smulaon

More information

IMPLEMENTATION OF FRACTURE MECHANICS CONCEPTS IN DYNAMIC PROGRESSIVE COLLAPSE PREDICTION USING AN OPTIMIZATION BASED ALGORITHM

IMPLEMENTATION OF FRACTURE MECHANICS CONCEPTS IN DYNAMIC PROGRESSIVE COLLAPSE PREDICTION USING AN OPTIMIZATION BASED ALGORITHM COMPDYN III ECCOMAS hema Conferene on Compuaonal Mehods n Sruural Dynams and Earhquake Engneerng M. Papadrakaks, M. Fragadaks, V. Plevrs (eds. Corfu, Greee, 5 8 May IMPLEMENAION OF FRACURE MECHANICS CONCEPS

More information

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration Naonal Exams December 205 04-BS-3 Bology 3 hours duraon NOTES: f doub exss as o he nerpreaon of any queson he canddae s urged o subm wh he answer paper a clear saemen of any assumpons made 2 Ths s a CLOSED

More information

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How about the more general linear scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )? lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of

More information

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION THE 19 TH INTERNATIONAL ONFERENE ON OMPOSITE MATERIALS ELASTI MODULUS ESTIMATION OF HOPPED ARBON FIBER TAPE REINFORED THERMOPLASTIS USING THE MONTE ARLO SIMULATION Y. Sao 1*, J. Takahash 1, T. Masuo 1,

More information

Brander and Lewis (1986) Link the relationship between financial and product sides of a firm.

Brander and Lewis (1986) Link the relationship between financial and product sides of a firm. Brander and Lews (1986) Lnk the relatonshp between fnanal and produt sdes of a frm. The way a frm fnanes ts nvestment: (1) Debt: Borrowng from banks, n bond market, et. Debt holders have prorty over a

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae

More information

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer d Model Cvl and Surveyng Soware Dranage Analyss Module Deenon/Reenon Basns Owen Thornon BE (Mech), d Model Programmer owen.hornon@d.com 4 January 007 Revsed: 04 Aprl 007 9 February 008 (8Cp) Ths documen

More information

Optimal Transform: The Karhunen-Loeve Transform (KLT)

Optimal Transform: The Karhunen-Loeve Transform (KLT) Opimal ransform: he Karhunen-Loeve ransform (KL) Reall: We are ineresed in uniary ransforms beause of heir nie properies: energy onservaion, energy ompaion, deorrelaion oivaion: τ (D ransform; assume separable)

More information

DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL

DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL Sco Wsdom, John Hershey 2, Jonahan Le Roux 2, and Shnj Waanabe 2 Deparmen o Elecrcal Engneerng, Unversy o Washngon, Seale, WA, USA

More information

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture Supersruure-asedOpmaonforDesgnof OpmalPSACylesforCO 2 Capure R. S. Kamah I. E. Grossmann L.. Begler Deparmen of Chemal Engneerng Carnege Mellon Unversy Psurgh PA 523 Marh 2 PSA n Nex Generaon Power Plans

More information

Chapters 2 Kinematics. Position, Distance, Displacement

Chapters 2 Kinematics. Position, Distance, Displacement Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g

More information

Performance Comparison of Bivariate Copulas on the CUSUM and EWMA Control Charts

Performance Comparison of Bivariate Copulas on the CUSUM and EWMA Control Charts Proeedngs of he World Congress on Engneerng and Compuer Sene 5 Vol II WCECS 5, Oober -3, 5, San Franso, USA Performane Comparson of Bvarae Copulas on he CUSUM and EWMA Conrol Chars Sasgarn Kuvaana, Saowan

More information

2.1 Constitutive Theory

2.1 Constitutive Theory Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +

More information

On computing differential transform of nonlinear non-autonomous functions and its applications

On computing differential transform of nonlinear non-autonomous functions and its applications On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,

More information

A Triple State Time Variant Cost Function Unit Commitment with Significant Vehicle to Grid Penetration

A Triple State Time Variant Cost Function Unit Commitment with Significant Vehicle to Grid Penetration 43 Inernaonal Journal of Smar Eleral Engneerng Vol.6 No.4 Fall 7 ISSN: 5-946 pp. 43:5 EISSN: 345-6 A Trple Sae Tme Varan Cos Funon n Commmen w Sgnfan Vele o Grd eneraon Moreza Aen * Aboulfazl Esmael Mamud

More information

Chapter 5. Circuit Theorems

Chapter 5. Circuit Theorems Chaper 5 Crcu Theorems Source Transformaons eplace a olage source and seres ressor by a curren and parallel ressor Fgure 5.-1 (a) A nondeal olage source. (b) A nondeal curren source. (c) Crcu B-conneced

More information

EEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment

EEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment EEL 6266 Power Sysem Operaon and Conrol Chaper 5 Un Commmen Dynamc programmng chef advanage over enumeraon schemes s he reducon n he dmensonaly of he problem n a src prory order scheme, here are only N

More information

Midterm Exam. Thursday, April hour, 15 minutes

Midterm Exam. Thursday, April hour, 15 minutes Economcs of Grow, ECO560 San Francsco Sae Unvers Mcael Bar Sprng 04 Mderm Exam Tursda, prl 0 our, 5 mnues ame: Insrucons. Ts s closed boo, closed noes exam.. o calculaors of an nd are allowed. 3. Sow all

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary

More information

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data Anne Chao Ncholas J Goell C seh lzabeh L ander K Ma Rober K Colwell and Aaron M llson 03 Rarefacon and erapolaon wh ll numbers: a framewor for samplng and esmaon n speces dversy sudes cology Monographs

More information

Hybrid probabilistic interval dynamic analysis of vehicle-bridge interaction system with uncertainties

Hybrid probabilistic interval dynamic analysis of vehicle-bridge interaction system with uncertainties 1 APCOM & SCM 11-14 h Deember, 13, Singapore Hybrid probabilisi inerval dynami analysis of vehile-bridge ineraion sysem wih unerainies Nengguang iu 1, * Wei Gao 1, Chongmin Song 1 and Nong Zhang 1 Shool

More information