LEADER 05273nam 2200625 a 450 001 9910463331503321 005 20200520144314.0 010 $a1-299-18870-2 010 $a1-118-50618-9 010 $a1-118-50617-0 035 $a(CKB)2670000000327720 035 $a(EBL)1120846 035 $a(OCoLC)810039791 035 $a(MiAaPQ)EBC1120846 035 $a(CaSebORM)9781118506172 035 $a(PPN)172649471 035 $a(Au-PeEL)EBL1120846 035 $a(CaPaEBR)ebr10657847 035 $a(CaONFJC)MIL450120 035 $a(EXLCZ)992670000000327720 100 $a20120914d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModel building in mathematical programming$b[electronic resource] /$fH. Paul Williams 205 $a5th ed. 210 $aHoboken, N.J. $cWiley$d2013 215 $a1 online resource (433 p.) 300 $aDescription based upon print version of record. 311 $a1-118-44333-0 320 $aIncludes bibliographical references and indexes. 327 $aCover; Title Page; Copyright; Contents; Preface; Part I; Chapter 1 Introduction; 1.1 The concept of a model; 1.2 Mathematical programming models; Chapter 2 Solving mathematical programming models; 2.1 Algorithms and packages; 2.1.1 Reduction; 2.1.2 Starting solutions; 2.1.3 Simple bounding constraints; 2.1.4 Ranged constraints; 2.1.5 Generalized upper bounding constraints; 2.1.6 Sensitivity analysis; 2.2 Practical considerations; 2.3 Decision support and expert systems; 2.4 Constraint programming (CP); Chapter 3 Building linear programming models; 3.1 The importance of linearity 327 $a3.2 Defining objectives3.2.1 Single objectives; 3.2.2 Multiple and conflicting objectives; 3.2.3 Minimax objectives; 3.2.4 Ratio objectives; 3.2.5 Non-existent and non-optimizable objectives; 3.3 Defining constraints; 3.3.1 Productive capacity constraints; 3.3.2 Raw material availabilities; 3.3.3 Marketing demands and limitations; 3.3.4 Material balance (continuity) constraints; 3.3.5 Quality stipulations; 3.3.6 Hard and soft constraints; 3.3.7 Chance constraints; 3.3.8 Conflicting constraints; 3.3.9 Redundant constraints; 3.3.10 Simple and generalized upper bounds; 3.3.11 Unusual constraints 327 $a3.4 How to build a good model3.4.1 Ease of understanding the model; 3.4.2 Ease of detecting errors in the model; 3.4.3 Ease of computing the solution; 3.4.4 Modal formulation; 3.4.5 Units of measurement; 3.5 The use of modelling languages; 3.5.1 A more natural input format; 3.5.2 Debugging is made easier; 3.5.3 Modification is made easier; 3.5.4 Repetition is automated; 3.5.5 Special purpose generators using a high level language; 3.5.6 Matrix block building systems; 3.5.7 Data structuring systems; 3.5.8 Mathematical languages; 3.5.8.1 SETs; 3.5.8.2 DATA; 3.5.8.3 VARIABLES; 3.5.8.4 OBJECTIVE 327 $a3.5.8.5 CONSTRAINTSChapter 4 Structured linear programming models; 4.1 Multiple plant, product and period models; 4.2 Stochastic programmes; 4.3 Decomposing a large model; 4.3.1 The submodels; 4.3.2 The restricted master model; Chapter 5 Applications and special types of mathematical programming model; 5.1 Typical applications; 5.1.1 The petroleum industry; 5.1.2 The chemical industry; 5.1.3 Manufacturing industry; 5.1.4 Transport and distribution; 5.1.5 Finance; 5.1.6 Agriculture; 5.1.7 Health; 5.1.8 Mining; 5.1.9 Manpower planning; 5.1.10 Food; 5.1.11 Energy; 5.1.12 Pulp and paper 327 $a5.1.13 Advertising5.1.14 Defence; 5.1.15 The supply chain; 5.1.16 Other applications; 5.2 Economic models; 5.2.1 The static model; 5.2.2 The dynamic model; 5.2.3 Aggregation; 5.3 Network models; 5.3.1 The transportation problem; 5.3.2 The assignment problem; 5.3.3 The transhipment problem; 5.3.4 The minimum cost flow problem; 5.3.5 The shortest path problem; 5.3.6 Maximum flow through a network; 5.3.7 Critical path analysis; 5.4 Converting linear programs to networks; Chapter 6 Interpreting and using the solution of a linear programming model; 6.1 Validating a model; 6.1.1 Infeasible models 327 $a6.1.2 Unbounded models 330 $aThe 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts. Suggested formulations and solutions are given together with some computational experience to give the reader a feel for the computational difficulty of solving that particular type of model. Furthermore, this book illustrates the scope and limitations of mathematical programming, and shows how it can be applied 606 $aProgramming (Mathematics) 606 $aMathematical models 608 $aElectronic books. 615 0$aProgramming (Mathematics) 615 0$aMathematical models. 676 $a519.7 686 $a519.7 WIL 700 $aWilliams$b H. P$028053 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910463331503321 996 $aModel building in mathematical programming$9331287 997 $aUNINA