"The editors draw on the expertise of researchers and application specialists from throughout the world."--Choice"This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems engineering, U. of Florida) and Resende (research scientist, AT&T Laboratories) present 26 chapters in which expert contributors discuss algorithms (linear, semidefinite, quadratic, nonlinear, stochastic, and integer programming), combinatorial optimization,deterministic global optimization, decomposition methods for mathematical programming, network and hierarchical optimization, artificial neural networks and parallel algorithms in optimization, complementaryand related problems, data envelopment analysis, and randomization in discrete optimization. They also cover applications (problem types, application areas) and software."--SciTech Book News

• Preface Panos M. Pardalos and Mauricio G. C. Resende: Introduction Panos M. Pardalos and Mauricio G. C. Resende: Part One: Algorithms 1: Linear Programming 1.1: Tamás Terlaky: Introduction 1.2: Tamás Terlaky: Simplex-Type Algorithms 1.3: Kees Roos: Interior-Point Methods for Linear Optimization 2: Henry Wolkowicz: Semidefinite Programming 3: Combinatorial Optimization 3.1: Panos M. Pardalos and Mauricio G. C. Resende: Introduction 3.2: Eva K. Lee: Branch-and-Bound Methods 3.3: John E. Mitchell: Branch-and-Cut Algorithms for Combinatorial Optimization Problems 3.4: Augustine O. Esogbue: Dynamic Programming Approaches 3.5: Mutsunori Yagiura and Toshihide Ibaraki: Local Search 3.6: Metaheuristics 3.6.1: Bruce L. Golden and Edward A. Wasil: Introduction 3.6.2: Éric D. Taillard: Ant Systems 3.6.3: John E. Beasley: Population Heuristics 3.6.4: Pablo Moscato: Memetic Algorithms 3.6.5: Leonidas S. Pitsoulis and Mauricio G. C. Resende: Greedy Randomized Adaptive Search Procedures 3.6.6: Manuel Laguna: Scatter Search 3.6.7: Fred Glover and Manuel Laguna: Tabu Search 3.6.8: E. H. L. Aarts and H. M. M. Ten Eikelder: Simulated Annealing 3.6.9: Pierre Hansen and Nenad Mladenovi'c: Variable Neighborhood Search 4: Yinyu Ye: Quadratic Programming 5: Nonlinear Programming 5.1: Gianni Di Pillo and Laura Palagi: Introduction 5.2: Gianni Di Pillo and Laura Palagi: Unconstrained Nonlinear Programming 5.3: Constrained Nonlinear Programming }a Gianni Di Pillo and Laura Palagi 5.4: Manlio Gaudioso: Nonsmooth Optimization 6: Christodoulos A. Floudas: Deterministic Global Optimizatio and Its Applications 7: Philippe Mahey: Decomposition Methods for Mathematical Programming 8: Network Optimization 8.1: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Introduction 8.2: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Maximum Flow Problem 8.3: Edith Cohen: Shortest-Path Algorithms 8.4: S. Thomas McCormick: Minimum-Cost Single-Commodity Flow 8.5: Pierre Chardaire and Abdel Lisser: Minimum-Cost Multicommodity Flow 8.6: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Minimum Spanning Tree Problem 9: Integer Programming 9.1: Nelson Maculan: Introduction 9.2: Nelson Maculan: Linear 0-1 Programming 9.3: Yves Crama and peter L. Hammer: Psedo-Boolean Optimization 9.4: Christodoulos A. Floudas: Mixed-Integer Nonlinear Optimization 9.5: Monique Guignard: Lagrangian Relaxation 9.6: Arne Løokketangen: Heuristics for 0-1 Mixed-Integer Programming 10: Theodore B. Trafalis and Suat Kasap: Artificial Neural Networks in Optimization and Applications 11: John R. Birge: Stochastic Programming 12: Hoang Tuy: Hierarchical Optimization 13: Michael C. Ferris and Christian Kanzow: Complementarity and Related Problems 14: José H. Dulá: Data Envelopment Analysis 15: Yair Censor and Stavros A. Zenios: Parallel Algorithms in Optimization 16: Sanguthevar Rajasekaran: Randomization in Discrete Optimization: Annealing Algorithms Part Two: Applications 17: Problem Types 17.1: Chung-Yee Lee and Michael Pinedo: Optimization and Heuristics of Scheduling 17.2: John E. Beasley, Abilio Lucena, and Marcus Poggi de Aragão: The Vehicle Routing Problem 17.3: Ding-Zhu Du: Network Designs: Approximations for Steiner Minimum Trees 17.4: Edward G. Coffman, Jr., János Csirik, and Gerhard J. Woeginger: Approximate Solutions to Bin Packing Problems 17.5: Rainer E. Burkard: The Traveling Salesmand Problem 17.6: Dukwon Kim and Boghos D. Sivazlian: Inventory Management 17.7: Zvi Drezner: Location 17.8: Jun Gu, Paul W. Purdom, John Franco, and Benjamin W. Wah: Algorithms for the Satisfiability (SAT) Problem 17.9: Eranda Çela: Assignment Problems 18: Application Areas 18.1: Warren B. Powell: Transportation and Logistics 18.2: Gang Yu and Benjamin G. Thengvall: Airline Optimization 18.3: Alexandra M. Newman, Linda K. Nozick, and Candace Arai Yano: Optimization in the Rail Industry 18.4: Andrés Weintraub Pohorille and John Hof: Forstry Industry 18.5: Stephen C. Graves: Manufacturing Planning and Control 18.6: Robert C. Leachman: Semiconductor Production Planning 18.7: Matthew E. Berge, John T. Betts, Sharon K. Filipowski, William P. Huffman, and David P. Young: Optimization in the Aerospace Industry 18.8: Energy 18.8.1: Gerson Couto de Oliveira, Sergio Granville, and Mario Pereira: Optimization in Electrical Power Systems 18.8.2: Roland N. Horne: Optimization Applications in Oil and Gas Recovery 18.8.3: Roger Z. Rios-Mercado: Natural Gas Pipeline Optimization 18.9: G. Anandalingam: Opimization of Telecommunications Networks 18.10: Stanislav Uryasev: Optimization of Test Intervals in Nuclear Engineering 18.11: Hussein A. Y. Etawil and Anthony Vannelli: Optimization in VLSI Design: Target Distance Models for Cell Placement 18.12: Michael Florian and Donald W. Hearn: Optimization Models in Transportation Planning 18.13: Guoliang Xue: Optimization in computation Molecular Biology 18.14: Anna Nagurney: Optimization in the Financial Services Industry 18.15: J. B. Rosen, John H. Glick, and E. Michael Gertz: Applied Large-Scale Nonlinear Optimization for Optimal Control of Partial Differential Equations and Differential Algebraic Equations 18.16: Kumaraswamy Ponnambalam: Optimization in Water Reservoir Systems 18.17: Ivan Dimov and Zahari Zlatev: Optimization Problems in Air-Pollution Modeling 18.18: Charles B. Moss: Applied Optimization in Agriculture 18.19: Petra Mutzel: Optimization in Graph Drawing 18.20: G. E. Stavroulakis: Optimization for Modeling of Nonlinear Interactions in Mechanics Part Three: Software 19: Emmanuel Fragnière and Jacek Gondzio: Optimization Modeling Languages 20: Stephen J. Wright: Optimization Software Packages 21: Andreas Fink, Stefan VoB, and David L. Woodruff: Optimization Software Libraries 22: John E. Beasley: Optimization Test Problem Libraries 23: Simone de L. Martins, Celso C. Ribeiro, and Noemi Rodriguez: Parallel Computing Environment 24: Catherine C. McGeoch: Experimental Analysis of Optimization Algorithms 25: Andreas Fink, Stefan VoB, and David L. Woodruff: Object-Oriented Programming 26: Michael A. Trick: Optimization and the Internet Directory of Contributors Index

"The editors draw on the expertise of researchers and application specialists from throughout the world."--Choice"This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems engineering, U. of Florida) and Resende (research scientist, AT&T Laboratories) present 26 chapters in which expert contributors discuss algorithms (linear, semidefinite, quadratic, nonlinear, stochastic, and integer programming), combinatorial optimization,deterministic global optimization, decomposition methods for mathematical programming, network and hierarchical optimization, artificial neural networks and parallel algorithms in optimization, complementaryand related problems, data envelopment analysis, and randomization in discrete optimization. They also cover applications (problem types, application areas) and software."--SciTech Book News

• Preface Panos M. Pardalos and Mauricio G. C. Resende: Introduction Panos M. Pardalos and Mauricio G. C. Resende: Part One: Algorithms 1: Linear Programming 1.1: Tamás Terlaky: Introduction 1.2: Tamás Terlaky: Simplex-Type Algorithms 1.3: Kees Roos: Interior-Point Methods for Linear Optimization 2: Henry Wolkowicz: Semidefinite Programming 3: Combinatorial Optimization 3.1: Panos M. Pardalos and Mauricio G. C. Resende: Introduction 3.2: Eva K. Lee: Branch-and-Bound Methods 3.3: John E. Mitchell: Branch-and-Cut Algorithms for Combinatorial Optimization Problems 3.4: Augustine O. Esogbue: Dynamic Programming Approaches 3.5: Mutsunori Yagiura and Toshihide Ibaraki: Local Search 3.6: Metaheuristics 3.6.1: Bruce L. Golden and Edward A. Wasil: Introduction 3.6.2: Éric D. Taillard: Ant Systems 3.6.3: John E. Beasley: Population Heuristics 3.6.4: Pablo Moscato: Memetic Algorithms 3.6.5: Leonidas S. Pitsoulis and Mauricio G. C. Resende: Greedy Randomized Adaptive Search Procedures 3.6.6: Manuel Laguna: Scatter Search 3.6.7: Fred Glover and Manuel Laguna: Tabu Search 3.6.8: E. H. L. Aarts and H. M. M. Ten Eikelder: Simulated Annealing 3.6.9: Pierre Hansen and Nenad Mladenovi'c: Variable Neighborhood Search 4: Yinyu Ye: Quadratic Programming 5: Nonlinear Programming 5.1: Gianni Di Pillo and Laura Palagi: Introduction 5.2: Gianni Di Pillo and Laura Palagi: Unconstrained Nonlinear Programming 5.3: Constrained Nonlinear Programming }a Gianni Di Pillo and Laura Palagi 5.4: Manlio Gaudioso: Nonsmooth Optimization 6: Christodoulos A. Floudas: Deterministic Global Optimizatio and Its Applications 7: Philippe Mahey: Decomposition Methods for Mathematical Programming 8: Network Optimization 8.1: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Introduction 8.2: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Maximum Flow Problem 8.3: Edith Cohen: Shortest-Path Algorithms 8.4: S. Thomas McCormick: Minimum-Cost Single-Commodity Flow 8.5: Pierre Chardaire and Abdel Lisser: Minimum-Cost Multicommodity Flow 8.6: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Minimum Spanning Tree Problem 9: Integer Programming 9.1: Nelson Maculan: Introduction 9.2: Nelson Maculan: Linear 0-1 Programming 9.3: Yves Crama and peter L. Hammer: Psedo-Boolean Optimization 9.4: Christodoulos A. Floudas: Mixed-Integer Nonlinear Optimization 9.5: Monique Guignard: Lagrangian Relaxation 9.6: Arne Løokketangen: Heuristics for 0-1 Mixed-Integer Programming 10: Theodore B. Trafalis and Suat Kasap: Artificial Neural Networks in Optimization and Applications 11: John R. Birge: Stochastic Programming 12: Hoang Tuy: Hierarchical Optimization 13: Michael C. Ferris and Christian Kanzow: Complementarity and Related Problems 14: José H. Dulá: Data Envelopment Analysis 15: Yair Censor and Stavros A. Zenios: Parallel Algorithms in Optimization 16: Sanguthevar Rajasekaran: Randomization in Discrete Optimization: Annealing Algorithms Part Two: Applications 17: Problem Types 17.1: Chung-Yee Lee and Michael Pinedo: Optimization and Heuristics of Scheduling 17.2: John E. Beasley, Abilio Lucena, and Marcus Poggi de Aragão: The Vehicle Routing Problem 17.3: Ding-Zhu Du: Network Designs: Approximations for Steiner Minimum Trees 17.4: Edward G. Coffman, Jr., János Csirik, and Gerhard J. Woeginger: Approximate Solutions to Bin Packing Problems 17.5: Rainer E. Burkard: The Traveling Salesmand Problem 17.6: Dukwon Kim and Boghos D. Sivazlian: Inventory Management 17.7: Zvi Drezner: Location 17.8: Jun Gu, Paul W. Purdom, John Franco, and Benjamin W. Wah: Algorithms for the Satisfiability (SAT) Problem 17.9: Eranda Çela: Assignment Problems 18: Application Areas 18.1: Warren B. Powell: Transportation and Logistics 18.2: Gang Yu and Benjamin G. Thengvall: Airline Optimization 18.3: Alexandra M. Newman, Linda K. Nozick, and Candace Arai Yano: Optimization in the Rail Industry 18.4: Andrés Weintraub Pohorille and John Hof: Forstry Industry 18.5: Stephen C. Graves: Manufacturing Planning and Control 18.6: Robert C. Leachman: Semiconductor Production Planning 18.7: Matthew E. Berge, John T. Betts, Sharon K. Filipowski, William P. Huffman, and David P. Young: Optimization in the Aerospace Industry 18.8: Energy 18.8.1: Gerson Couto de Oliveira, Sergio Granville, and Mario Pereira: Optimization in Electrical Power Systems 18.8.2: Roland N. Horne: Optimization Applications in Oil and Gas Recovery 18.8.3: Roger Z. Rios-Mercado: Natural Gas Pipeline Optimization 18.9: G. Anandalingam: Opimization of Telecommunications Networks 18.10: Stanislav Uryasev: Optimization of Test Intervals in Nuclear Engineering 18.11: Hussein A. Y. Etawil and Anthony Vannelli: Optimization in VLSI Design: Target Distance Models for Cell Placement 18.12: Michael Florian and Donald W. Hearn: Optimization Models in Transportation Planning 18.13: Guoliang Xue: Optimization in computation Molecular Biology 18.14: Anna Nagurney: Optimization in the Financial Services Industry 18.15: J. B. Rosen, John H. Glick, and E. Michael Gertz: Applied Large-Scale Nonlinear Optimization for Optimal Control of Partial Differential Equations and Differential Algebraic Equations 18.16: Kumaraswamy Ponnambalam: Optimization in Water Reservoir Systems 18.17: Ivan Dimov and Zahari Zlatev: Optimization Problems in Air-Pollution Modeling 18.18: Charles B. Moss: Applied Optimization in Agriculture 18.19: Petra Mutzel: Optimization in Graph Drawing 18.20: G. E. Stavroulakis: Optimization for Modeling of Nonlinear Interactions in Mechanics Part Three: Software 19: Emmanuel Fragnière and Jacek Gondzio: Optimization Modeling Languages 20: Stephen J. Wright: Optimization Software Packages 21: Andreas Fink, Stefan VoB, and David L. Woodruff: Optimization Software Libraries 22: John E. Beasley: Optimization Test Problem Libraries 23: Simone de L. Martins, Celso C. Ribeiro, and Noemi Rodriguez: Parallel Computing Environment 24: Catherine C. McGeoch: Experimental Analysis of Optimization Algorithms 25: Andreas Fink, Stefan VoB, and David L. Woodruff: Object-Oriented Programming 26: Michael A. Trick: Optimization and the Internet Directory of Contributors Index

"The editors draw on the expertise of researchers and application specialists from throughout the world."--Choice"This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems engineering, U. of Florida) and Resende (research scientist, AT&T Laboratories) present 26 chapters in which expert contributors discuss algorithms (linear, semidefinite, quadratic, nonlinear, stochastic, and integer programming), combinatorial optimization,deterministic global optimization, decomposition methods for mathematical programming, network and hierarchical optimization, artificial neural networks and parallel algorithms in optimization, complementaryand related problems, data envelopment analysis, and randomization in discrete optimization. They also cover applications (problem types, application areas) and software."--SciTech Book News

• Preface Panos M. Pardalos and Mauricio G. C. Resende: Introduction Panos M. Pardalos and Mauricio G. C. Resende: Part One: Algorithms 1: Linear Programming 1.1: Tamás Terlaky: Introduction 1.2: Tamás Terlaky: Simplex-Type Algorithms 1.3: Kees Roos: Interior-Point Methods for Linear Optimization 2: Henry Wolkowicz: Semidefinite Programming 3: Combinatorial Optimization 3.1: Panos M. Pardalos and Mauricio G. C. Resende: Introduction 3.2: Eva K. Lee: Branch-and-Bound Methods 3.3: John E. Mitchell: Branch-and-Cut Algorithms for Combinatorial Optimization Problems 3.4: Augustine O. Esogbue: Dynamic Programming Approaches 3.5: Mutsunori Yagiura and Toshihide Ibaraki: Local Search 3.6: Metaheuristics 3.6.1: Bruce L. Golden and Edward A. Wasil: Introduction 3.6.2: Éric D. Taillard: Ant Systems 3.6.3: John E. Beasley: Population Heuristics 3.6.4: Pablo Moscato: Memetic Algorithms 3.6.5: Leonidas S. Pitsoulis and Mauricio G. C. Resende: Greedy Randomized Adaptive Search Procedures 3.6.6: Manuel Laguna: Scatter Search 3.6.7: Fred Glover and Manuel Laguna: Tabu Search 3.6.8: E. H. L. Aarts and H. M. M. Ten Eikelder: Simulated Annealing 3.6.9: Pierre Hansen and Nenad Mladenovi'c: Variable Neighborhood Search 4: Yinyu Ye: Quadratic Programming 5: Nonlinear Programming 5.1: Gianni Di Pillo and Laura Palagi: Introduction 5.2: Gianni Di Pillo and Laura Palagi: Unconstrained Nonlinear Programming 5.3: Constrained Nonlinear Programming }a Gianni Di Pillo and Laura Palagi 5.4: Manlio Gaudioso: Nonsmooth Optimization 6: Christodoulos A. Floudas: Deterministic Global Optimizatio and Its Applications 7: Philippe Mahey: Decomposition Methods for Mathematical Programming 8: Network Optimization 8.1: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Introduction 8.2: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Maximum Flow Problem 8.3: Edith Cohen: Shortest-Path Algorithms 8.4: S. Thomas McCormick: Minimum-Cost Single-Commodity Flow 8.5: Pierre Chardaire and Abdel Lisser: Minimum-Cost Multicommodity Flow 8.6: Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin: Minimum Spanning Tree Problem 9: Integer Programming 9.1: Nelson Maculan: Introduction 9.2: Nelson Maculan: Linear 0-1 Programming 9.3: Yves Crama and peter L. Hammer: Psedo-Boolean Optimization 9.4: Christodoulos A. Floudas: Mixed-Integer Nonlinear Optimization 9.5: Monique Guignard: Lagrangian Relaxation 9.6: Arne Løokketangen: Heuristics for 0-1 Mixed-Integer Programming 10: Theodore B. Trafalis and Suat Kasap: Artificial Neural Networks in Optimization and Applications 11: John R. Birge: Stochastic Programming 12: Hoang Tuy: Hierarchical Optimization 13: Michael C. Ferris and Christian Kanzow: Complementarity and Related Problems 14: José H. Dulá: Data Envelopment Analysis 15: Yair Censor and Stavros A. Zenios: Parallel Algorithms in Optimization 16: Sanguthevar Rajasekaran: Randomization in Discrete Optimization: Annealing Algorithms Part Two: Applications 17: Problem Types 17.1: Chung-Yee Lee and Michael Pinedo: Optimization and Heuristics of Scheduling 17.2: John E. Beasley, Abilio Lucena, and Marcus Poggi de Aragão: The Vehicle Routing Problem 17.3: Ding-Zhu Du: Network Designs: Approximations for Steiner Minimum Trees 17.4: Edward G. Coffman, Jr., János Csirik, and Gerhard J. Woeginger: Approximate Solutions to Bin Packing Problems 17.5: Rainer E. Burkard: The Traveling Salesmand Problem 17.6: Dukwon Kim and Boghos D. Sivazlian: Inventory Management 17.7: Zvi Drezner: Location 17.8: Jun Gu, Paul W. Purdom, John Franco, and Benjamin W. Wah: Algorithms for the Satisfiability (SAT) Problem 17.9: Eranda Çela: Assignment Problems 18: Application Areas 18.1: Warren B. Powell: Transportation and Logistics 18.2: Gang Yu and Benjamin G. Thengvall: Airline Optimization 18.3: Alexandra M. Newman, Linda K. Nozick, and Candace Arai Yano: Optimization in the Rail Industry 18.4: Andrés Weintraub Pohorille and John Hof: Forstry Industry 18.5: Stephen C. Graves: Manufacturing Planning and Control 18.6: Robert C. Leachman: Semiconductor Production Planning 18.7: Matthew E. Berge, John T. Betts, Sharon K. Filipowski, William P. Huffman, and David P. Young: Optimization in the Aerospace Industry 18.8: Energy 18.8.1: Gerson Couto de Oliveira, Sergio Granville, and Mario Pereira: Optimization in Electrical Power Systems 18.8.2: Roland N. Horne: Optimization Applications in Oil and Gas Recovery 18.8.3: Roger Z. Rios-Mercado: Natural Gas Pipeline Optimization 18.9: G. Anandalingam: Opimization of Telecommunications Networks 18.10: Stanislav Uryasev: Optimization of Test Intervals in Nuclear Engineering 18.11: Hussein A. Y. Etawil and Anthony Vannelli: Optimization in VLSI Design: Target Distance Models for Cell Placement 18.12: Michael Florian and Donald W. Hearn: Optimization Models in Transportation Planning 18.13: Guoliang Xue: Optimization in computation Molecular Biology 18.14: Anna Nagurney: Optimization in the Financial Services Industry 18.15: J. B. Rosen, John H. Glick, and E. Michael Gertz: Applied Large-Scale Nonlinear Optimization for Optimal Control of Partial Differential Equations and Differential Algebraic Equations 18.16: Kumaraswamy Ponnambalam: Optimization in Water Reservoir Systems 18.17: Ivan Dimov and Zahari Zlatev: Optimization Problems in Air-Pollution Modeling 18.18: Charles B. Moss: Applied Optimization in Agriculture 18.19: Petra Mutzel: Optimization in Graph Drawing 18.20: G. E. Stavroulakis: Optimization for Modeling of Nonlinear Interactions in Mechanics Part Three: Software 19: Emmanuel Fragnière and Jacek Gondzio: Optimization Modeling Languages 20: Stephen J. Wright: Optimization Software Packages 21: Andreas Fink, Stefan VoB, and David L. Woodruff: Optimization Software Libraries 22: John E. Beasley: Optimization Test Problem Libraries 23: Simone de L. Martins, Celso C. Ribeiro, and Noemi Rodriguez: Parallel Computing Environment 24: Catherine C. McGeoch: Experimental Analysis of Optimization Algorithms 25: Andreas Fink, Stefan VoB, and David L. Woodruff: Object-Oriented Programming 26: Michael A. Trick: Optimization and the Internet Directory of Contributors Index