THREE DIMENSIONAL FIXED CHARGE BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION PROBLEM *

Size: px
Start display at page:

Download "THREE DIMENSIONAL FIXED CHARGE BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION PROBLEM *"

Transcription

1 Yugoslav Joural of Oeratios Research (), Nuber, - THREE DIMENSIONAL FIXED CHARGE BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION PROBLEM S.R. ARORA Deartet of Matheatics, Has Raj College, Uiversity of Delhi Delhi-, Idia. srarora@yahoo.co Archaa KHURANA Deartet of Matheatics, Uiversity of Delhi, Delhi-, Idia archaa@rediffail.co, archaa@du.ac.i Received: October / Acceted: August Abstract: The three-diesioal fixed charge trasortatio roble is a extesio of the classical three-diesioal trasortatio roble i which a fixed cost is icurred for every origi. I the reset aer three-diesioal fixed charge bi-criterio idefiite quadratic trasortatio roble, givig the sae riority to cost as well as tie, is studied. A algorith to fid the efficiet cost-tie trade off airs i a three diesioal fixed charge bi-criterio idefiite quadratic trasortatio roble is develoed. The algorith is illustrated with the hel of a uerical exale. Keywords: Three diesioal quadratic trasortatio roble, cost-tie trade-off airs, fixed charge, bi-criterio idefiite quadratic trasortatio roble. INTRODUCTION I the classical trasortatio roble the cost of trasortatio is directly roortioal to the uber of uits of the coodity trasorted. But i real world situatios whe a coodity is trasorted, a fixed cost is icurred i the objective fuctio. The fixed cost ay rereset the cost of retig a vehicle, ladig fees i a airort, set u costs for achies i a aufacturig eviroet etc. Matheatics Subject Classificatio: Priary: B; Secodary: C

2 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge The fixed charge trasortatio roble was origially forulated by G.B.Datzig ad W. Hirsch [] i. The i K.G.Murty [] solved the fixed charge roble by rakig the extree oits. After that several rocedures for solvig fixed charge trasortatio robles were develoed. Soeties there ay exist eergecy situatios such as fire services, abulace services, olice services etc. whe the tie of trasortatio is of greater iortace tha the cost of trasortatio. Several ethods [, ] for iiizig the tie of trasortatio are also develoed. I Bhatia [] et.al. rovided the tie-cost trade-off airs i a liear trasortatio roble. Also i Basu et. al.[] develoed a algorith for the otiu tie-cost trade-off i a fixed charge liear trasortatio roble givig sae riority to cost ad tie. The trasortatio roble cosidered i the classical trasortatio roble is geerally a two-diesioal liear trasortatio roble. Haley [] i described the solutio of a liear ulti-idex trasortatio roble where there are three idices. The ethod for solutio reseted by Haley is a extesio of MODI ethod. I, Basu et al. [] rovided a algorith for fidig the otiu solutio of the solid fixed charge liear trasortatio roble. I this aer three diesioal fixed charge bi-criterio idefiite quadratic trasortatio roble, givig the sae riority to cost ad tie, is studied. A algorith to idetify the efficiet cost-tie trade-off airs for the roble is develoed.. PROBLEM FORMULATION Suose i =,,..., are the origis j =,,..., are the destiatios ad k =,,..., are the various tyes of coodities to be trasorted i a three diesioal trasortatio roble. Let x = the aout of kth tye of coodity trasorted for the ith origi to the jth destiatio c = the variable cost er uit aout of the kth tye of coodity trasorted fro the ith origi to the jth destiatio which is ideedet of the aout of the coodity trasorted, so log as x > d = the er uit dereciatio cost (wear ad tear or daaged cost) of the kth tye of coodity trasorted fro the ith origi to the jth destiatio, which is ideedet of the aout of coodity trasorted, so log as x >. A jk = the total quatity of kth tye of the coodity received by jth destiatio fro all the sources B ki = the total quatity of the kth tye of the coodity available at the ith origi to be sulied to all destiatios

3 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge E ij = the total quatity of all tyes of coodities to be sulied fro ith origi to the jth destiatio. The the three diesioal trasortatio roble is defied as i Z subject to c x i= j= k= = (P ) x = Ajk, =,,...,, =,,..., i= j k x = Bki, =,,...,, =,,..., j= k i x = Eij, =,,...,, =,,..., k = i j x, i =,,...,, j =,,...,, k =,,..., Here, there are origis, destiatios ad tyes of coodities to be trasorted. Also, Ajk = Bki, k,,..., j= i= Bki = Eij, i,,..., k= j= Eij = Ajk, j,,..., i= k= = (i) = (ii) jk ki ij j= k= k= i= i= j= = (ii) A = B = E (iv) (i) ilies kth tye of coodity received by all destiatios = kth tye of coodity sulied fro all origis. (ii) ilies differet tyes of coodities sulied by the ith source = aout of coodities received by all destiatios fro the ith source (iii) ilies aout of coodities sulied fro all sources to jth destiatio = differet tyes of coodities received by the jth destiatio. (iv) ilies aout of coodities received by all destiatios of differet tyes of coodities = aout of coodities sulied fro all origis to all destiatios = aout of differet tyes of coodities sulied fro all origis.

4 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Note: (i) to (iv) idicates that the trasortatio roble (P ) cosidered is a balaced trasortatio roble. Now let, F ik = the fixed cost associated with origi i ad the kth tye of coodity. We defie F ik accordig to the aout sulied as where δ F = F δ, i =,,...,, k =,,..., ik j= if x >, = if x =,, i =,,...,, j =,,...,, k =,,..., Now, cosider the three diesioal fixed charge bi-criterio idefiite quadratic trasortatio roble as subject to i c x d x + Fik, ax[ t / x > ] i i= j= k= i= j= k= i= k= j k (P ) x = Ajk, =,,...,, =,,..., i= j k x = Bki, =,,...,, =,,..., j= k i x = Eij, =,,...,, =,,..., k = i j x, i =,,...,, j =,,...,, k =,,..., Also, () Ajk = Bki, k =,,..., j= i= Bki = Eij, i =,,..., k= j= Eij = Ajk, j =,,..., i= k= A = B = E jk ki ij j= k= k= i= i= j=

5 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge I the roble (P ), we eed to iiize the trasortatio cost ad dereciatio cost siultaeously of the kth tye of the roduct to be trasorted fro the ith origi to jth destiatio. Also we eed to iiize the total cost (variable cost + fixed cost) ad the total tie of trasortatio. Therefore we have cosidered the objective fuctio of the for as i roble (P ).. THEORETICAL DEVELOPMENT: To solve the roble (P ) we searate it ito two robles (P' ) ad (P" ) as i Z = c x d x + Fik i= j= k= i= j= k= i= k= subject to () (P' ) i T = ax[ t / x > ] subject to () (P" ) i j k To obtai the set of efficiet cost-tie trade off airs, we first solve (P' ) ad read the tie with resect to the iiu cost Z where tie T is give by the roble (P" ). At the first iteratio, let Z be the iiu total cost of the roble (P' ) ad T be the otial tie of the roble (P" ) with resect to is coleted earlier tha T would cost ore tha Z. So Z, the ay schedule which ( Z, T ) is called the tiecost trade off air at the first iteratio. After odifyig the costs with resect to the tie obtaied, a ew otial cost is obtaied ad tie is read with resect to the ew otial cost. This rocedure is called re-otiizatio rocedure. Let after qth iteratio, the solutio be ifeasible. Thus we get the followig colete set of tie cost trade off airs, ( Z, T ), ( Z, T ), ( Z, T ),, ( Z, T ) q q where Z < Z < Z < < Z q ad T > T > T > >. T q The airs so defied are areto-otial solutios of the give roble. The we idetify the iiu cost Z ad iiu tie T q aog the above trade-off airs. The air ( Z, T q ) with iiu cost ad iiu tie is tered as the ideal solutio which ca ot be achieved i ractical situatios.

6 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Cosider a three diesioal quadratic trasortatio roble as i Z = c x d x i= j= k= i= j= k= subject to (P ) x = Ajk, =,,...,, =,,..., i= j k x = Bki, =,,...,, =,,..., j= k i x = Eij, =,,...,, =,,..., k = i j ad x, i =,,...,, j =,,...,, k =,,..., Theore. Let X = { x } be a basic feasible solutio of roble (P ) with basis atrix B. The it will be a otial basic feasible solutio if where R, cells (, i j, k) B =, cells (, i j, k) B R = θ ( z d )( z c ) Z ( z d ) Z ( z c ) ujk + vki + wij = z, cells (, i j, k) B u + v + = z, cells (, i j, k) B jk ki ij Also ujk + vki + wij = c, cells (, i j, k) B u + v + = d, cells (, i j, k) B () jk ki ij Z be the value of c x i j k at the curret basic feasible solutio corresodig to basis atrix B. Z be the value of d x at the curret basic feasible solutio corresodig i j k to basis atrix B. θ is the level at which a o-basic cell (, i j, k ) eters the basis relacig soe basic cell of B.

7 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Note: u, v, w, u, v, are deteried by usig equatios () ad takig jk ki ij jk ki ij + + of the u jk s or v ki s or w ij s ad u jk s or v ki s or ij s as zero. Proof: Let Z be the objective fuctio value of the roble (P ). Let Z = ZZ Let Ẑ be the value of the objective fuctio at the curret basic feasible solutio Xˆ = { x } corresodig to the basis B obtaied o eterig the cell (, i j, k ) ito the basis. The Z ˆ = [ Z ( )][ ( )] + θ c z Z + θ d z Now, ˆ = [ + θ ( )][ + θ ( )] = ZZ + Zθ ( d z ) + Zθ ( c z ) + θ ( c z )( d z ) ZZ = Zθ ( d z ) + Zθ ( c z ) + θ ( c z )( d z ) = θ[ Z( d z ) + Z( c z ) + θ ( c z )( d z )] Z Z Z c z Z d z Z Z This basic feasible solutio will give a iroved value of Z if Ẑ < Z. i.e., if ˆ Z Z < i.e., if θ[ Z( d z ) + Z( c z ) + θ ( c z ) < ( d z )] < sice θ [ Z ( d z ) + Z ( c z ) + θ ( c z )( d z )] < () Oe ca ove fro oe basic feasible solutio to aother basic feasible solutio o eterig the cell (, i j, k ) ito the basis for which coditio () is satisfied. It will be a otial basic feasible solutio if θ ( z d )( z c ) Z ( z d ) Z ( z c ) or R cells (, i j, k) B where R = θ ( z d )( z c ) Z( z d ) Z( z c ) Also, it ca easily be see that R = cells (, i j, k) B ALGORITHM: Ste : Fid the iitial basic feasible solutio of the roble (P' ). Ste : Calculate the fixed cost of the curret basic feasible solutio ad deote this by F (curret), where F (curret) = i= k= Ste : Calculate R cells (, i j, k) B, B is the curret basis. where R = θ ( z d )( z c ) Z( z d ) Z( z c ) F ik

8 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge ad ujk + vki + wij = z cells (, i j, k) B u + v + = z cells (, i j, k) B jk ki ij Ste : Fid A = R E where A is the chage i cost that occurs o itroducig a o-basic cell (, i j, k ) with value E ( (, i j, k) B) ito the basis. Ste : Fid F (Differece) = F (NB) F (curret) where F (NB) is the total fixed cost ivolved o itroducig the variable x with values ( E ) ( (, i j, k) B) ito the curret basis to for a ew basis. Ste : Calculate = F (Differece) + A ( (, i j, k) B) Ste : If all Let its iiu be the go to ste, otherwise fid i{ /, (,, ) } qr. The cell ( qr,, ) eters the basis. Go to ste. Ste : Let Z be the otial cost of (P' ) ad corresodig to Z. Ste : Fid T = ax{ t / x > } M if t T Ste : Defie c =, c if t < T < i j k B. X be the otial solutio of (P' ) where M is a sufficietly large ositive uber. Ste : Fid a basic feasible solutio of the roble (P' ) with resect to the ew variable costs c. Go to ste ad reeat the rocess. Ste : Let after the qth iteratio, the solutio is ifeasible. The idetify the colete set of efficiet cost tie trade off airs. subject to. NUMERICAL ILLUSTRATION Cosider a three diesioal fixed charge bi-criterio trasortatio roble. i c x d x + Fik, ax[ t / x > ] i i= j= k= i= j= k= i= k= j k (P) i= x x j= = A = B jk ki

9 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge x k = = E ij x where A = B = E jk ki ij j= k= k= i= i= j= The data of variable cost c ad tie t is give Table ad Table ' resectively. c d Table. j = j = j = B ki i = E = E = E = i = E = E = E = i = E = E = E = A jk

10 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge The fixed costs are F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = F =, F =, F = Table '. t i = i = i = j= j= j= Usig the North-West Corer Rule, we fid the iitial basic feasible solutio of roble (P) as give i Table.

11 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Table. j = j = j = F (Basic) c w = () w = - (-) w = - v d () (-) (-) - v (-) i= () () (-) = () () = - () = - () w = () w = w = () (-) () i= () () () = () = () = () u +v +w c (-) w = () w = - () w = u + v + w -d () i= () () () = () = (-) (-) = (-) (-) - - u u -

12 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Here, Z =, Z = Table. (i,j,k) (,,) (,,) (,,) (,,) (,,) (,,) (,,) (,,) A = R E No - No No = - = loo = = = - loo loo F (Diff.) - - = A + F (Diff.) - - Here, i{ / <, ( i, j, k) B} = i{, } = cell (,,) eters the basis. We fid the ew solutio. Reeat the rocess. The otial basic feasible solutio is give i Table.

13 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Table. j = j = j = F (Basic) w = () w = () w = v i= () (-) (-) - v () () () = () = - (-) () = - () - () w = - () w = () w = - (-) - i= () () () (-) - = (-) (-) = - () = () - () w = () w = () w = i= () () () () (-) (-) = = (-) = (-) u u

14 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Here, Z =, Z = Table. (i,j,k) (,,) (,,) (,,) (,,) (,,) (,,) (,,) (,,) A = R E No No = No = loo = loo loo = F (Diff.) - - = A + F (Diff.) Sice, (, i j, k) B we sto. The otial value of Z = Z = + = ad the corresodig tie T =. The first cost-tie trade off air is (, ). Defie c M, t T = = c, t < T =. ad for the ew three diesioal quadratic trasortatio roble. O solvig this roble the ext trade off air is ( Z, T ) = (, ). Proceedig like this, we get the third cost-tie trade-off air as ( Z, T ) = (, ). After that the roble defied at tie T becoes ifeasible. Hece the tie-cost trade-off airs are (, ), (, ) ad (, ). Coclusio. For fidig efficiet cost-tie trade off airs i a three-diesioal idefiite quadratic trasortatio roble (A) First we iiize total cost (variable cost + fixed cost) ad the iiize tie with resect to iiu cost obtaied ad for the first cost-tie trade-off air. (B) Next after odifyig cost with resect to the tie obtaied i the last result we agai iiize cost, read the corresodig tie ad for the ext cost-tie trade-off air. (C) Therefore we kee o icreasig the cost ad readig the tie o each ste ad fid the efficiet cost-tie trade off airs. (B) is reeated util the roble becoes ifeasible. Reark.. A alterative aroach to solve roble (P ) is to first iiize the tie fuctio ad the read the corresodig cost (variable + fixed) fro the solutio which gives the iiu tie. Thereafter, we kee o icreasig the tie steadily ad readig the cost at each ste. We cotiue till the solutio becoes ifeasible.. Proble (P' ) caot be solved by the ethod develoed for liear trasortatio roble as the variable δ takes the value or. So we first fid the basic feasible solutio of the roble (P ) ad the calculate the corresodig fixed charge.

15 S.R. Arora, A. Khuraa / Three Diesioal Fixed Charge Ackowledgeets:. The authors are grateful to referees for their valuable coets ad suggestios.. The author Ms. Archaa Khuraa is also grateful to Coucil of Scietific ad Idustrial Research, New Delhi for the fiacial assistace. REFERENCES [] Ahuja, A., ad Arora, S.R., Multi-idex fixed charge bi-criterio trasortatio roble, Idia Joural of Pure ad Alied Matheatics, () () -. [] Basu, M., Pal, B.B., ad Kudu, A., A algorith for otiu tie-cost trade-off i fixed charge bi-criterio trasortatio roble, Otiizatio, () -. [] Basu, M., Pal, B.B., ad Kudu, A., A algorith for fidig the otiu solutio of solid fixed-charge trasortatio roble, () -. [] Bhatia, H.L., Swaroo, K., ad Puri, M.C., Tie-cost trade-off i a trasortatio roble, Osearch, () -. [] Bhatia, H.L., Swaroo, K., ad Puri, M.C., A rocedure for tie iiizatio trasortatio roble, Idia Joural of Pure ad Alied Matheatics, () -. [] Haley, K.B, The solid trasortatio roble, Oeratios Research, () -. [] Haley, K.B., The ulti-idex roble, Oeratios Research, () -. [] Haer, Peter, L., Tie-iiizig trasortatio robles, Naval Research Logistics Quarterly, () -. [] Hirsch, W.M., ad Datzig, G.B., Notes o liear rograig: Part XIX, The fixed charge roble, Rad Research Meoradu No., Sata Moica, Califoria,. [] Kuh, H., ad Bauol, W., "A aroxiate algorith for the fixed-charge trasortatio roble", Naval Research Logistics Quarterly, () -. [] Murty, K. G., Solvig the fixed-charge roble by rakig the extree oits, Oeratios Research, () -. [] Raakrisha, C.S, A ote o the tie iiizig trasortatio roble, Osearch, () -. [] Sadagoa, S., ad Ravidra, A., A vertex rakig algorith for the fixed-charge trasortatio roble, Joural of Otiizatio Theory ad Alicatios, () -. [] Sadrock, K., A sile algorith for solvig sall fixed-charge trasortatio robles, Joural of the Oeratioal Research Society, () -. [] Steiberg, D.I., The fixed-charge roble, Naval Research Logistics Quarterly, () -. [] Szwarc, W., Soe rearks o the tie trasortatio roble, Naval Research Logistics Quarterly, () -.

Modified Method for Fixed Charge Transportation Problem

Modified Method for Fixed Charge Transportation Problem Iteratioal Joural of Egieerig Ivetios e-issn: 2278-7461, p-issn: 219-6491 Volue, Issue1 (August 201) PP: 67-71 Modified Method for Fixed Charge Trasportatio Proble Debiprasad Acharya b, Majusri Basu a

More information

MULTI-INDEX FIXED CHARGE BI-CRITERION TRANSPORTATION PROBLEM. Mathematics and Computing. Deepika Gupta Roll no

MULTI-INDEX FIXED CHARGE BI-CRITERION TRANSPORTATION PROBLEM. Mathematics and Computing. Deepika Gupta Roll no MULTI-INDEX FIXED CHARGE BI-CRITERION TRANSPORTATION PROBLEM Thesis subitted i partial fulfillet of the requireet for The award of the degree of Masters of Sciece I Matheatics ad Coputig Subitted by Deepika

More information

S. A. ALIEV, Y. I. YELEYKO, Y. V. ZHERNOVYI. STEADY-STATE DISTRIBUTIONS FOR CERTAIN MODIFICATIONS OF THE M/M/1/m QUEUEING SYSTEM

S. A. ALIEV, Y. I. YELEYKO, Y. V. ZHERNOVYI. STEADY-STATE DISTRIBUTIONS FOR CERTAIN MODIFICATIONS OF THE M/M/1/m QUEUEING SYSTEM Trasactios of Azerbaija Natioal Acadey of Scieces, Series of Physical-Techical ad Matheatical Scieces: Iforatics ad Cotrol Probles 009 Vol XXIX, 6 P 50-58 S A ALIEV, Y I YELEYKO, Y V ZHERNOVYI STEADY-STATE

More information

FUZZY TRANSPORTATION PROBLEM WITH ADDITIONAL RESTRICTIONS

FUZZY TRANSPORTATION PROBLEM WITH ADDITIONAL RESTRICTIONS VOL. 5, NO. 2, FEBRUARY 200 ISSN 89-6608 ARPN Joural of Egieerig ad Applied Scieces 2006-200 Asia Research Publishig Network (ARPN). All rights reserved. www.arpjourals.co FUZZY TRANSPORTATION PROBLEM

More information

8.3 Perturbation theory

8.3 Perturbation theory 8.3 Perturbatio theory Slides: Video 8.3.1 Costructig erturbatio theory Text referece: Quatu Mechaics for Scietists ad gieers Sectio 6.3 (u to First order erturbatio theory ) Perturbatio theory Costructig

More information

Introduction to Optimization, DIKU Monday 19 November David Pisinger. Duality, motivation

Introduction to Optimization, DIKU Monday 19 November David Pisinger. Duality, motivation Itroductio to Optiizatio, DIKU 007-08 Moday 9 Noveber David Pisiger Lecture, Duality ad sesitivity aalysis Duality, shadow prices, sesitivity aalysis, post-optial aalysis, copleetary slackess, KKT optiality

More information

Birth-Death Processes. Outline. EEC 686/785 Modeling & Performance Evaluation of Computer Systems. Relationship Among Stochastic Processes.

Birth-Death Processes. Outline. EEC 686/785 Modeling & Performance Evaluation of Computer Systems. Relationship Among Stochastic Processes. EEC 686/785 Modelig & Perforace Evaluatio of Couter Systes Lecture Webig Zhao Deartet of Electrical ad Couter Egieerig Clevelad State Uiversity webig@ieee.org based o Dr. Raj jai s lecture otes Relatioshi

More information

On Order of a Function of Several Complex Variables Analytic in the Unit Polydisc

On Order of a Function of Several Complex Variables Analytic in the Unit Polydisc ISSN 746-7659, Eglad, UK Joural of Iforatio ad Coutig Sciece Vol 6, No 3, 0, 95-06 O Order of a Fuctio of Several Colex Variables Aalytic i the Uit Polydisc Rata Kuar Dutta + Deartet of Matheatics, Siliguri

More information

Primes of the form n 2 + 1

Primes of the form n 2 + 1 Itroductio Ladau s Probles are four robles i Nuber Theory cocerig rie ubers: Goldbach s Cojecture: This cojecture states that every ositive eve iteger greater tha ca be exressed as the su of two (ot ecessarily

More information

THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION

THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION MATHEMATICA MONTISNIGRI Vol XXVIII (013) 17-5 THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION GLEB V. FEDOROV * * Mechaics ad Matheatics Faculty Moscow State Uiversity Moscow, Russia

More information

AVERAGE MARKS SCALING

AVERAGE MARKS SCALING TERTIARY INSTITUTIONS SERVICE CENTRE Level 1, 100 Royal Street East Perth, Wester Australia 6004 Telephoe (08) 9318 8000 Facsiile (08) 95 7050 http://wwwtisceduau/ 1 Itroductio AVERAGE MARKS SCALING I

More information

The Hypergeometric Coupon Collection Problem and its Dual

The Hypergeometric Coupon Collection Problem and its Dual Joural of Idustrial ad Systes Egieerig Vol., o., pp -7 Sprig 7 The Hypergeoetric Coupo Collectio Proble ad its Dual Sheldo M. Ross Epstei Departet of Idustrial ad Systes Egieerig, Uiversity of Souther

More information

Automated Proofs for Some Stirling Number Identities

Automated Proofs for Some Stirling Number Identities Autoated Proofs for Soe Stirlig Nuber Idetities Mauel Kauers ad Carste Scheider Research Istitute for Sybolic Coputatio Johaes Kepler Uiversity Altebergerstraße 69 A4040 Liz, Austria Subitted: Sep 1, 2007;

More information

LP in Standard and Slack Forms

LP in Standard and Slack Forms LP i Stadard ad Slack Fors ax j=1 s.t. j=1 c j a ij b i for i=1, 2,..., 0 for j=1, 2,..., z = 0 j=1 c j x i = b i j=1 a ij for i=1, 2,..., Auxiliary Liear Progra L: LP i stadard for: ax j=1 L aux : Auxiliary

More information

Binomial transform of products

Binomial transform of products Jauary 02 207 Bioial trasfor of products Khristo N Boyadzhiev Departet of Matheatics ad Statistics Ohio Norther Uiversity Ada OH 4580 USA -boyadzhiev@ouedu Abstract Give the bioial trasfors { b } ad {

More information

SOME PROPERTIES OF CERTAIN MULTIVALENT ANALYTIC FUNCTIONS USING A DIFFERENTIAL OPERATOR

SOME PROPERTIES OF CERTAIN MULTIVALENT ANALYTIC FUNCTIONS USING A DIFFERENTIAL OPERATOR Joural of the Alied Matheatics Statistics ad Iforatics (JAMSI) 5 (9) No SOME PROPERTIES OF CERTAIN MULTIVALENT ANALYTIC FUNCTIONS USING A DIFFERENTIAL OPERATOR SP GOYAL AND RAKESH KUMAR Abstract Here we

More information

NUMERICAL METHODS FOR SOLVING EQUATIONS

NUMERICAL METHODS FOR SOLVING EQUATIONS Mathematics Revisio Guides Numerical Methods for Solvig Equatios Page 1 of 11 M.K. HOME TUITION Mathematics Revisio Guides Level: GCSE Higher Tier NUMERICAL METHODS FOR SOLVING EQUATIONS Versio:. Date:

More information

Necessary Optimality Conditions for a Class of Nonsmooth Vector Optimization Problems Xuan-wei ZHOU *

Necessary Optimality Conditions for a Class of Nonsmooth Vector Optimization Problems Xuan-wei ZHOU * 28 Iteratioal Coferece o Modelig, Siulatio ad Otiizatio (MSO 28) ISBN: 978--6595-542- Necessary Otiality Coditios for a Class of Nosooth Vector Otiizatio Probles Xua-wei ZHOU * School of Basic Courses,

More information

GENERALIZED KERNEL AND MIXED INTEGRAL EQUATION OF FREDHOLM - VOLTERRA TYPE R. T. Matoog

GENERALIZED KERNEL AND MIXED INTEGRAL EQUATION OF FREDHOLM - VOLTERRA TYPE R. T. Matoog GENERALIZED KERNEL AND MIXED INTEGRAL EQUATION OF FREDHOLM - VOLTERRA TYPE R. T. Matoog Assistat Professor. Deartet of Matheatics, Faculty of Alied Scieces,U Al-Qura Uiversity, Makkah, Saudi Arabia Abstract:

More information

International Journal of Mathematical Archive-4(9), 2013, 1-5 Available online through ISSN

International Journal of Mathematical Archive-4(9), 2013, 1-5 Available online through   ISSN Iteratioal Joural o Matheatical Archive-4(9), 03, -5 Available olie through www.ija.io ISSN 9 5046 THE CUBIC RATE OF CONVERGENCE OF GENERALIZED EXTRAPOLATED NEWTON RAPHSON METHOD FOR SOLVING NONLINEAR

More information

Songklanakarin Journal of Science and Technology SJST R1 Teerapabolarn

Songklanakarin Journal of Science and Technology SJST R1 Teerapabolarn Soglaaari Joural of Sciece ad Techology SJST--.R Teeraabolar A No-uiform Boud o Biomial Aroimatio to the Beta Biomial Cumulative Distributio Fuctio Joural: Soglaaari Joural of Sciece ad Techology For Review

More information

Special Modeling Techniques

Special Modeling Techniques Colorado School of Mies CHEN43 Secial Modelig Techiques Secial Modelig Techiques Summary of Toics Deviatio Variables No-Liear Differetial Equatios 3 Liearizatio of ODEs for Aroximate Solutios 4 Coversio

More information

An Application of Generalized Bessel Functions on Certain Subclasses of Analytic Functions

An Application of Generalized Bessel Functions on Certain Subclasses of Analytic Functions Turkish Joural of Aalysis ad Nuber Theory, 5, Vol 3, No, -6 Available olie at htt://ubsscieubco/tjat/3// Sciece ad Educatio ublishig DOI:69/tjat-3-- A Alicatio of Geeralized Bessel Fuctios o Certai Subclasses

More information

15.093J Optimization Methods. Lecture 22: Barrier Interior Point Algorithms

15.093J Optimization Methods. Lecture 22: Barrier Interior Point Algorithms 1593J Otimizatio Methods Lecture : Barrier Iterior Poit Algorithms 1 Outlie 1 Barrier Methods Slide 1 The Cetral Path 3 Aroximatig the Cetral Path 4 The Primal Barrier Algorithm 5 The Primal-Dual Barrier

More information

A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM

A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM *Kore B. G. Departmet Of Statistics, Balwat College, VITA - 415 311, Dist.: Sagli (M. S.). Idia *Author for Correspodece ABSTRACT I this paper I

More information

The Method of Least Squares. To understand least squares fitting of data.

The Method of Least Squares. To understand least squares fitting of data. The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve

More information

Linear Programming and the Simplex Method

Linear Programming and the Simplex Method Liear Programmig ad the Simplex ethod Abstract This article is a itroductio to Liear Programmig ad usig Simplex method for solvig LP problems i primal form. What is Liear Programmig? Liear Programmig is

More information

Confidence Intervals

Confidence Intervals Cofidece Itervals Berli Che Deartmet of Comuter Sciece & Iformatio Egieerig Natioal Taiwa Normal Uiversity Referece: 1. W. Navidi. Statistics for Egieerig ad Scietists. Chater 5 & Teachig Material Itroductio

More information

SYMMETRIC POSITIVE SEMI-DEFINITE SOLUTIONS OF AX = B AND XC = D

SYMMETRIC POSITIVE SEMI-DEFINITE SOLUTIONS OF AX = B AND XC = D Joural of Pure ad Alied Mathematics: Advaces ad Alicatios olume, Number, 009, Pages 99-07 SYMMERIC POSIIE SEMI-DEFINIE SOLUIONS OF AX B AND XC D School of Mathematics ad Physics Jiagsu Uiversity of Sciece

More information

The ELECTRE Multicriteria Analysis Approach Based on Intuitionistic Fuzzy Sets

The ELECTRE Multicriteria Analysis Approach Based on Intuitionistic Fuzzy Sets The ELETRE Multicriteria alysis roach Based o Ituitioistic Fuzzy Sets Mig-he Wu ad Tig-Yu he bstract Over the last decades, ituitioistic fuzzy sets have bee alied to ay differet fields, such as logic rograig,

More information

[ 47 ] then T ( m ) is true for all n a. 2. The greatest integer function : [ ] is defined by selling [ x]

[ 47 ] then T ( m ) is true for all n a. 2. The greatest integer function : [ ] is defined by selling [ x] [ 47 ] Number System 1. Itroductio Pricile : Let { T ( ) : N} be a set of statemets, oe for each atural umber. If (i), T ( a ) is true for some a N ad (ii) T ( k ) is true imlies T ( k 1) is true for all

More information

Transshipment Problem using Modified Neural Network Model

Transshipment Problem using Modified Neural Network Model Trasshipet Proble usig Modified Neural Networ Model N. C. Ashioba Departet of Coputer Sciece Delta State Polytechic Ogwashi Uu, Delta State, Nigeria. E. O. Nwachuwu Departet of Coputer Sciece Uiversity

More information

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018 CSE 353 Discrete Computatioal Structures Sprig 08 Sequeces, Mathematical Iductio, ad Recursio (Chapter 5, Epp) Note: some course slides adopted from publisher-provided material Overview May mathematical

More information

Discrete Mathematics: Lectures 8 and 9 Principle of Inclusion and Exclusion Instructor: Arijit Bishnu Date: August 11 and 13, 2009

Discrete Mathematics: Lectures 8 and 9 Principle of Inclusion and Exclusion Instructor: Arijit Bishnu Date: August 11 and 13, 2009 Discrete Matheatics: Lectures 8 ad 9 Priciple of Iclusio ad Exclusio Istructor: Arijit Bishu Date: August ad 3, 009 As you ca observe by ow, we ca cout i various ways. Oe such ethod is the age-old priciple

More information

THE CAPACIATED TRANSPORTATION PROBLEM IN LINEAR FRACTIONAL FUNCTIONALS PROGRAMMING

THE CAPACIATED TRANSPORTATION PROBLEM IN LINEAR FRACTIONAL FUNCTIONALS PROGRAMMING J. Operations Research Soc. of Japan VoJ. 10, Nos. I & 2 October 1967 1967 The Operations Research Society of Japan THE CAPACIATED TRANSPORTATION PROBLEM IN LINEAR FRACTIONAL FUNCTIONALS PROGRAMMING SURESH

More information

Some remarks on the paper Some elementary inequalities of G. Bennett

Some remarks on the paper Some elementary inequalities of G. Bennett Soe rears o the paper Soe eleetary iequalities of G. Beett Dag Ah Tua ad Luu Quag Bay Vieta Natioal Uiversity - Haoi Uiversity of Sciece Abstract We give soe couterexaples ad soe rears of soe of the corollaries

More information

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting Statistics ad Data Aalysis i MATLAB Kedrick Kay, kedrick.kay@wustl.edu February 28, 2014 Lecture 4: Model fittig 1. The basics - Suppose that we have a set of data ad suppose that we have selected the

More information

19.1 The dictionary problem

19.1 The dictionary problem CS125 Lecture 19 Fall 2016 19.1 The dictioary proble Cosider the followig data structural proble, usually called the dictioary proble. We have a set of ites. Each ite is a (key, value pair. Keys are i

More information

arxiv: v1 [math.nt] 26 Feb 2014

arxiv: v1 [math.nt] 26 Feb 2014 FROBENIUS NUMBERS OF PYTHAGOREAN TRIPLES BYUNG KEON GIL, JI-WOO HAN, TAE HYUN KIM, RYUN HAN KOO, BON WOO LEE, JAEHOON LEE, KYEONG SIK NAM, HYEON WOO PARK, AND POO-SUNG PARK arxiv:1402.6440v1 [ath.nt] 26

More information

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data Lecture 9 Curve fittig I Itroductio Suppose we are preseted with eight poits of easured data (x i, y j ). As show i Fig. o the left, we could represet the uderlyig fuctio of which these data are saples

More information

ECE534, Spring 2018: Final Exam

ECE534, Spring 2018: Final Exam ECE534, Srig 2018: Fial Exam Problem 1 Let X N (0, 1) ad Y N (0, 1) be ideedet radom variables. variables V = X + Y ad W = X 2Y. Defie the radom (a) Are V, W joitly Gaussia? Justify your aswer. (b) Comute

More information

Orthogonal Functions

Orthogonal Functions Royal Holloway Uiversity of odo Departet of Physics Orthogoal Fuctios Motivatio Aalogy with vectors You are probably failiar with the cocept of orthogoality fro vectors; two vectors are orthogoal whe they

More information

Optimization Methods MIT 2.098/6.255/ Final exam

Optimization Methods MIT 2.098/6.255/ Final exam Optimizatio Methods MIT 2.098/6.255/15.093 Fial exam Date Give: December 19th, 2006 P1. [30 pts] Classify the followig statemets as true or false. All aswers must be well-justified, either through a short

More information

Optimally Sparse SVMs

Optimally Sparse SVMs A. Proof of Lemma 3. We here prove a lower boud o the umber of support vectors to achieve geeralizatio bouds of the form which we cosider. Importatly, this result holds ot oly for liear classifiers, but

More information

Recurrence Relations

Recurrence Relations Recurrece Relatios Aalysis of recursive algorithms, such as: it factorial (it ) { if (==0) retur ; else retur ( * factorial(-)); } Let t be the umber of multiplicatios eeded to calculate factorial(). The

More information

2. F ; =(,1)F,1; +F,1;,1 is satised by thestirlig ubers of the rst kid ([1], p. 824). 3. F ; = F,1; + F,1;,1 is satised by the Stirlig ubers of the se

2. F ; =(,1)F,1; +F,1;,1 is satised by thestirlig ubers of the rst kid ([1], p. 824). 3. F ; = F,1; + F,1;,1 is satised by the Stirlig ubers of the se O First-Order Two-Diesioal Liear Hoogeeous Partial Dierece Equatios G. Neil Have y Ditri A. Gusev z Abstract Aalysis of algoriths occasioally requires solvig of rst-order two-diesioal liear hoogeeous partial

More information

A New Solution Method for the Finite-Horizon Discrete-Time EOQ Problem

A New Solution Method for the Finite-Horizon Discrete-Time EOQ Problem This is the Pre-Published Versio. A New Solutio Method for the Fiite-Horizo Discrete-Time EOQ Problem Chug-Lu Li Departmet of Logistics The Hog Kog Polytechic Uiversity Hug Hom, Kowloo, Hog Kog Phoe: +852-2766-7410

More information

AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION

AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION Joural of Statistics: Advaces i Theory ad Applicatios Volue 3, Nuber, 00, Pages 6-78 AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION Departet of Matheatics Brock Uiversity St. Catharies, Otario

More information

k-equitable mean labeling

k-equitable mean labeling Joural of Algorithms ad Comutatio joural homeage: htt://jac.ut.ac.ir k-euitable mea labelig P.Jeyathi 1 1 Deartmet of Mathematics, Govidammal Aditaar College for Wome, Tiruchedur- 628 215,Idia ABSTRACT

More information

Math 312 Lecture Notes One Dimensional Maps

Math 312 Lecture Notes One Dimensional Maps Math 312 Lecture Notes Oe Dimesioal Maps Warre Weckesser Departmet of Mathematics Colgate Uiversity 21-23 February 25 A Example We begi with the simplest model of populatio growth. Suppose, for example,

More information

Studying Interaction of Cotton-Raw Material with Working Bodies of Cotton-Cleaning Machines

Studying Interaction of Cotton-Raw Material with Working Bodies of Cotton-Cleaning Machines ISSN: 35-38 Iteratioal Joural of AdvacedResearch i Sciece, Egieerig ad Techology Vol. 5, Issue, Deceber 8 Studyig Iteractio of Cotto-Raw Material with Workig Bodies of Cotto-Cleaig Machies R.H. Rosulov,

More information

Problem. Consider the sequence a j for j N defined by the recurrence a j+1 = 2a j + j for j > 0

Problem. Consider the sequence a j for j N defined by the recurrence a j+1 = 2a j + j for j > 0 GENERATING FUNCTIONS Give a ifiite sequece a 0,a,a,, its ordiary geeratig fuctio is A : a Geeratig fuctios are ofte useful for fidig a closed forula for the eleets of a sequece, fidig a recurrece forula,

More information

A 2nTH ORDER LINEAR DIFFERENCE EQUATION

A 2nTH ORDER LINEAR DIFFERENCE EQUATION A 2TH ORDER LINEAR DIFFERENCE EQUATION Doug Aderso Departmet of Mathematics ad Computer Sciece, Cocordia College Moorhead, MN 56562, USA ABSTRACT: We give a formulatio of geeralized zeros ad (, )-discojugacy

More information

ECE534, Spring 2018: Solutions for Problem Set #2

ECE534, Spring 2018: Solutions for Problem Set #2 ECE534, Srig 08: s for roblem Set #. Rademacher Radom Variables ad Symmetrizatio a) Let X be a Rademacher radom variable, i.e., X = ±) = /. Show that E e λx e λ /. E e λx = e λ + e λ = + k= k=0 λ k k k!

More information

Classification of DT signals

Classification of DT signals Comlex exoetial A discrete time sigal may be comlex valued I digital commuicatios comlex sigals arise aturally A comlex sigal may be rereseted i two forms: jarg { z( ) } { } z ( ) = Re { z ( )} + jim {

More information

APPLICATION OF A PRECISE ANALOGUE IN SOLVING THE FUZZY PROBLEM OF OPTIMAL CONTROL FOR THE HYDRATION BLOCK

APPLICATION OF A PRECISE ANALOGUE IN SOLVING THE FUZZY PROBLEM OF OPTIMAL CONTROL FOR THE HYDRATION BLOCK WORLD SCIENCE ISSN 43-03 APPLICAION OF A PRECISE ANALOGUE IN SOLVING HE FUZZY PROBLEM OF OPIMAL CONROL FOR HE HYDRAION BLOCK Associated Professor Elchi Melikov Azerbaija, Baku, Azerbaija State Oil ad Idustr

More information

Metric Dimension of Some Graphs under Join Operation

Metric Dimension of Some Graphs under Join Operation Global Joural of Pure ad Applied Matheatics ISSN 0973-768 Volue 3, Nuber 7 (07), pp 333-3348 Research Idia Publicatios http://wwwripublicatioco Metric Diesio of Soe Graphs uder Joi Operatio B S Rawat ad

More information

Int. Journal of Math. Analysis, Vol. 6, 2012, no. 31, S. Panayappan

Int. Journal of Math. Analysis, Vol. 6, 2012, no. 31, S. Panayappan It Joural of Math Aalysis, Vol 6, 0, o 3, 53 58 O Power Class ( Operators S Paayappa Departet of Matheatics Goveret Arts College, Coibatore 6408 ailadu, Idia paayappa@gailco N Sivaai Departet of Matheatics

More information

FUZZY RELIABILITY ANALYSIS OF COMPOUND SYSTEM BASED ON WEIBULL DISTRIBUTION

FUZZY RELIABILITY ANALYSIS OF COMPOUND SYSTEM BASED ON WEIBULL DISTRIBUTION IJAMML 3:1 (2015) 31-39 Septeber 2015 ISSN: 2394-2258 Available at http://scietificadvaces.co.i DOI: http://dx.doi.org/10.18642/ijal_7100121530 FUZZY RELIABILITY ANALYSIS OF COMPOUND SYSTEM BASED ON WEIBULL

More information

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions ECE 9 Lecture 4: Estiatio of Lipschitz sooth fuctios R. Nowak 5/7/29 Cosider the followig settig. Let Y f (X) + W, where X is a rado variable (r.v.) o X [, ], W is a r.v. o Y R, idepedet of X ad satisfyig

More information

-ORDER CONVERGENCE FOR FINDING SIMPLE ROOT OF A POLYNOMIAL EQUATION

-ORDER CONVERGENCE FOR FINDING SIMPLE ROOT OF A POLYNOMIAL EQUATION NEW NEWTON-TYPE METHOD WITH k -ORDER CONVERGENCE FOR FINDING SIMPLE ROOT OF A POLYNOMIAL EQUATION R. Thukral Padé Research Cetre, 39 Deaswood Hill, Leeds West Yorkshire, LS7 JS, ENGLAND ABSTRACT The objective

More information

A Tabu Search Method for Finding Minimal Multi-Homogeneous Bézout Number

A Tabu Search Method for Finding Minimal Multi-Homogeneous Bézout Number Joural of Matheatics ad Statistics 6 (): 105-109, 010 ISSN 1549-3644 010 Sciece Publicatios A Tabu Search Method for Fidig Miial Multi-Hoogeeous Bézout Nuber Hassa M.S. Bawazir ad Ali Abd Raha Departet

More information

Putnam Training Exercise Counting, Probability, Pigeonhole Principle (Answers)

Putnam Training Exercise Counting, Probability, Pigeonhole Principle (Answers) Putam Traiig Exercise Coutig, Probability, Pigeohole Pricile (Aswers) November 24th, 2015 1. Fid the umber of iteger o-egative solutios to the followig Diohatie equatio: x 1 + x 2 + x 3 + x 4 + x 5 = 17.

More information

1 The Primal and Dual of an Optimization Problem

1 The Primal and Dual of an Optimization Problem CS 189 Itroductio to Machie Learig Fall 2017 Note 18 Previously, i our ivestigatio of SVMs, we forulated a costraied optiizatio proble that we ca solve to fid the optial paraeters for our hyperplae decisio

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

Bertrand s postulate Chapter 2

Bertrand s postulate Chapter 2 Bertrad s postulate Chapter We have see that the sequece of prie ubers, 3, 5, 7,... is ifiite. To see that the size of its gaps is ot bouded, let N := 3 5 p deote the product of all prie ubers that are

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

Properties and Tests of Zeros of Polynomial Functions

Properties and Tests of Zeros of Polynomial Functions Properties ad Tests of Zeros of Polyomial Fuctios The Remaider ad Factor Theorems: Sythetic divisio ca be used to fid the values of polyomials i a sometimes easier way tha substitutio. This is show by

More information

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Inverse Matrix. A meaning that matrix B is an inverse of matrix A. Iverse Matrix Two square matrices A ad B of dimesios are called iverses to oe aother if the followig holds, AB BA I (11) The otio is dual but we ofte write 1 B A meaig that matrix B is a iverse of matrix

More information

The Sumudu transform and its application to fractional differential equations

The Sumudu transform and its application to fractional differential equations ISSN : 30-97 (Olie) Iteratioal e-joural for Educatio ad Mathematics www.iejem.org vol. 0, No. 05, (Oct. 03), 9-40 The Sumudu trasform ad its alicatio to fractioal differetial equatios I.A. Salehbhai, M.G.

More information

Markov Decision Processes

Markov Decision Processes Markov Decisio Processes Defiitios; Statioary policies; Value improvemet algorithm, Policy improvemet algorithm, ad liear programmig for discouted cost ad average cost criteria. Markov Decisio Processes

More information

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions Nae Period ALGEBRA II Chapter B ad A Notes Solvig Iequalities ad Absolute Value / Nubers ad Fuctios SECTION.6 Itroductio to Solvig Equatios Objectives: Write ad solve a liear equatio i oe variable. Solve

More information

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20 ECE 6341 Sprig 016 Prof. David R. Jackso ECE Dept. Notes 0 1 Spherical Wave Fuctios Cosider solvig ψ + k ψ = 0 i spherical coordiates z φ θ r y x Spherical Wave Fuctios (cot.) I spherical coordiates we

More information

Essential Microeconomics EXISTENCE OF EQUILIBRIUM Core ideas: continuity of excess demand functions, Fixed point theorems

Essential Microeconomics EXISTENCE OF EQUILIBRIUM Core ideas: continuity of excess demand functions, Fixed point theorems Essetial Microecoomics -- 5.3 EXISTENCE OF EQUILIBRIUM Core ideas: cotiuity of excess demad fuctios, Fixed oit teorems Two commodity excage ecoomy 2 Excage ecoomy wit may commodities 5 Discotiuous demad

More information

GENERALIZED LEGENDRE POLYNOMIALS AND RELATED SUPERCONGRUENCES

GENERALIZED LEGENDRE POLYNOMIALS AND RELATED SUPERCONGRUENCES J. Nuber Theory 0, o., 9-9. GENERALIZED LEGENDRE POLYNOMIALS AND RELATED SUPERCONGRUENCES Zhi-Hog Su School of Matheatical Scieces, Huaiyi Noral Uiversity, Huaia, Jiagsu 00, PR Chia Eail: zhihogsu@yahoo.co

More information

VIETA-LIKE PRODUCTS OF NESTED RADICALS

VIETA-LIKE PRODUCTS OF NESTED RADICALS VIETA-IKE PRODUCTS OF ESTED RADICAS Thomas J. Osler athematics Deartmet Rowa Uiversity Glassboro, J 0808 Osler@rowa.edu Itroductio The beautiful ifiite roduct of radicals () π due to Vieta [] i 9, is oe

More information

ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND

ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND Pacific-Asia Joural of Mathematics, Volume 5, No., Jauary-Jue 20 ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND SHAKEEL JAVAID, Z. H. BAKHSHI & M. M. KHALID ABSTRACT: I this paper, the roll cuttig problem

More information

Progressive Review and Analytical Approach for Optimal Solution of Stochastic Transportation Problems (STP) Involving Multi-Choice Cost

Progressive Review and Analytical Approach for Optimal Solution of Stochastic Transportation Problems (STP) Involving Multi-Choice Cost Aerica Joural of Modelig ad Otiizatio, 204, Vol. 2, No. 3, 77-83 Available olie at htt://ubs.scieub.co/ajo/2/3/3 Sciece ad Educatio Publishig DOI:0.269/ajo-2-3-3 Progressive Review ad Aalytical Aroach

More information

A Note on the W-S Lower Bound of the MEE Estimation

A Note on the W-S Lower Bound of the MEE Estimation troy 014, 16, 814-84; doi:10.3390/e1600814 Article OPN ACCSS etroy ISSN 1099-4300 www.di.co/joural/etroy A Note o the W-S Lower Boud of the M stiatio Badog Che 1, *, Guagi Wag 1, Naig Zheg 1 ad Jose C.

More information

Refinements of Jensen s Inequality for Convex Functions on the Co-Ordinates in a Rectangle from the Plane

Refinements of Jensen s Inequality for Convex Functions on the Co-Ordinates in a Rectangle from the Plane Filoat 30:3 (206, 803 84 DOI 0.2298/FIL603803A Published by Faculty of Scieces ad Matheatics, Uiversity of Niš, Serbia Available at: http://www.pf.i.ac.rs/filoat Refieets of Jese s Iequality for Covex

More information

A Construction That Produces Wallis-Type Formulas

A Construction That Produces Wallis-Type Formulas Advaces i Pure Mathematics 03 3 579-585 htt://dxdoiorg/0436/am0336074 Published Olie Setember 03 (htt://scirorg/joural/am) A Costructio That Produces Wallis-Tye Formulas Joshua M Fitzhugh David L Farsorth

More information

E. Bashirova, N. Svobodina THE EVALUATION OF METAL OIL AND GAS EQUIPMENT IN A CURRENT CONDITION BY MEANS OF TRANSFER FUNCTION PARAMETERS

E. Bashirova, N. Svobodina THE EVALUATION OF METAL OIL AND GAS EQUIPMENT IN A CURRENT CONDITION BY MEANS OF TRANSFER FUNCTION PARAMETERS 1 УДК 62.179.14 E. Bashirova, N. Svobodia THE EVALUATION OF METAL OIL AND GAS EQUIPMENT IN A CURRENT CONDITION BY MEANS OF TRANSFER FUNCTION PARAMETERS The equiet used for oil refiig, dealig with highly

More information

On Some Identities and Generating Functions for Mersenne Numbers and Polynomials

On Some Identities and Generating Functions for Mersenne Numbers and Polynomials Turish Joural of Aalysis ad Number Theory, 8, Vol 6, No, 9-97 Available olie at htt://ubsscieubcom/tjat/6//5 Sciece ad Educatio Publishig DOI:69/tjat-6--5 O Some Idetities ad Geeratig Fuctios for Mersee

More information

The Differential Transform Method for Solving Volterra s Population Model

The Differential Transform Method for Solving Volterra s Population Model AASCIT Couicatios Volue, Issue 6 Septeber, 15 olie ISSN: 375-383 The Differetial Trasfor Method for Solvig Volterra s Populatio Model Khatereh Tabatabaei Departet of Matheatics, Faculty of Sciece, Kafas

More information

Define a Markov chain on {1,..., 6} with transition probability matrix P =

Define a Markov chain on {1,..., 6} with transition probability matrix P = Pla Group Work 0. The title says it all Next Tie: MCMC ad Geeral-state Markov Chais Midter Exa: Tuesday 8 March i class Hoework 4 due Thursday Uless otherwise oted, let X be a irreducible, aperiodic Markov

More information

Ratio of Two Random Variables: A Note on the Existence of its Moments

Ratio of Two Random Variables: A Note on the Existence of its Moments Metodološki zvezki, Vol. 3, o., 6, -7 Ratio of wo Rado Variables: A ote o the Existece of its Moets Ato Cedilik, Kataria Košel, ad Adre Bleec 3 Abstract o eable correct statistical iferece, the kowledge

More information

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1)

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1) Suer MA 1500 Lesso 1 Sectio 1.6, Sectio 1.7 (part 1) I Solvig Polyoial Equatios Liear equatio ad quadratic equatios of 1 variable are specific types of polyoial equatios. Soe polyoial equatios of a higher

More information

Chapter 2 The Solution of Numerical Algebraic and Transcendental Equations

Chapter 2 The Solution of Numerical Algebraic and Transcendental Equations Chapter The Solutio of Numerical Algebraic ad Trascedetal Equatios Itroductio I this chapter we shall discuss some umerical methods for solvig algebraic ad trascedetal equatios. The equatio f( is said

More information

SECTION 2.6 THE SECOND ALTERNATIVE

SECTION 2.6 THE SECOND ALTERNATIVE 54 SECTION 2.6 THE SECOND ALTERNATIVE We ow discuss the probles where the Secod Alterative holds. The suppositio is that there is a otrivial solutio for L(y) =, B (y) = B 2 (y) =. The Fredhol Theores assure

More information

X. Perturbation Theory

X. Perturbation Theory X. Perturbatio Theory I perturbatio theory, oe deals with a ailtoia that is coposed Ĥ that is typically exactly solvable of two pieces: a referece part ad a perturbatio ( Ĥ ) that is assued to be sall.

More information

PUTNAM TRAINING PROBABILITY

PUTNAM TRAINING PROBABILITY PUTNAM TRAINING PROBABILITY (Last udated: December, 207) Remark. This is a list of exercises o robability. Miguel A. Lerma Exercises. Prove that the umber of subsets of {, 2,..., } with odd cardiality

More information

Orthogonal transformations

Orthogonal transformations Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/21 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-25 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

MATH 10550, EXAM 3 SOLUTIONS

MATH 10550, EXAM 3 SOLUTIONS MATH 155, EXAM 3 SOLUTIONS 1. I fidig a approximate solutio to the equatio x 3 +x 4 = usig Newto s method with iitial approximatio x 1 = 1, what is x? Solutio. Recall that x +1 = x f(x ) f (x ). Hece,

More information

Random Models. Tusheng Zhang. February 14, 2013

Random Models. Tusheng Zhang. February 14, 2013 Radom Models Tusheg Zhag February 14, 013 1 Radom Walks Let me describe the model. Radom walks are used to describe the motio of a movig particle (object). Suppose that a particle (object) moves alog the

More information

International Journal of Multidisciplinary Research and Modern Education (IJMRME) ISSN (Online): (www.rdmodernresearch.

International Journal of Multidisciplinary Research and Modern Education (IJMRME) ISSN (Online): (www.rdmodernresearch. (wwwrdoderresearchco) Volue II, Issue II, 2016 PRODUC OPERAION ON FUZZY RANSIION MARICES V Chiadurai*, S Barkavi**, S Vayabalaji*** & J Parthiba**** * Departet of Matheatics, Aaalai Uiversity, Aaalai Nagar,

More information

How to Maximize a Function without Really Trying

How to Maximize a Function without Really Trying How to Maximize a Fuctio without Really Tryig MARK FLANAGAN School of Electrical, Electroic ad Commuicatios Egieerig Uiversity College Dubli We will prove a famous elemetary iequality called The Rearragemet

More information

CSCI-6971 Lecture Notes: Stochastic processes

CSCI-6971 Lecture Notes: Stochastic processes CSCI-6971 Lecture Notes: Stochastic processes Kristopher R. Beevers Departet of Coputer Sciece Resselaer Polytechic Istitute beevek@cs.rpi.edu February 2, 2006 1 Overview Defiitio 1.1. A stochastic process

More information

On the Fibonacci-like Sequences of Higher Order

On the Fibonacci-like Sequences of Higher Order Article Iteratioal Joural of oder atheatical Scieces, 05, 3(): 5-59 Iteratioal Joural of oder atheatical Scieces Joural hoepage: wwwoderscietificpressco/jourals/ijsaspx O the Fiboacci-like Sequeces of

More information

Lebesgue Constant Minimizing Bivariate Barycentric Rational Interpolation

Lebesgue Constant Minimizing Bivariate Barycentric Rational Interpolation Appl. Math. If. Sci. 8, No. 1, 187-192 (2014) 187 Applied Matheatics & Iforatio Scieces A Iteratioal Joural http://dx.doi.org/10.12785/ais/080123 Lebesgue Costat Miiizig Bivariate Barycetric Ratioal Iterpolatio

More information