Handbook of global optimization

著者

書誌事項

Handbook of global optimization

edited by Reiner Horst and Panos M. Pardalos

（Nonconvex optimization and its applications, v. 2, v. 62）

Kluwer Academic, c1995-c2002

  • [v. 1]
  • v. 2

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注記

Includes bibliographical references and index

Vol. 2 edited by Panos M. Pardalos and H. Edwin Romeijn

内容説明・目次

巻冊次

[v. 1] ISBN 9780792331209

内容説明

Global optimization is concerned with the computation and characterization of global optima of nonlinear functions. During the past three decades the field of global optimization has been growing at a rapid pace, and the number of publications on all aspects of global optimization has been increasing steadily. Many applications, as well as new theoretical, algorithmic, and computational contributions have resulted. The Handbook of Global Optimization is the first comprehensive book to cover recent developments in global optimization. Each contribution in the Handbook is essentially expository in nature, but scholarly in its treatment. The chapters cover optimality conditions, complexity results, concave minimization, DC programming, general quadratic programming, nonlinear complementarity, minimax problems, multiplicative programming, Lipschitz optimization, fractional programming, network problems, trajectory methods, homotopy methods, interval methods, and stochastic approaches. The Handbook of Global Optimization is addressed to researchers in mathematical programming, as well as all scientists who use optimization methods to model and solve problems.

目次

  • Preface. 1. Conditions for Global Optimality
  • J.-B. Hiriart-Urruty. 2. Complexity Issues in Global Optimization: a Survey
  • S.A. Vavasis. 3. Concave Minimization: Theory, Applications and Algorithms
  • H.P. Benson. 4. DC Optimization: Theory, Methods and Algorithms
  • Hoang Tuy. 5. Quadratic Optimization
  • C.A. Floudas, V. Visweswaran. 6. Complementary Problems
  • Jong-Shi Pang. 7. Minimax and its Applications
  • Ding-Zhu Du. 8. Multiplicative Programming Problems
  • H. Konno, T. Kuno. 9. Lipschitz Optimization
  • P. Hansen, B. Jaumard. 10. Fractional Programming
  • S. Schaible. 11. Network Problems
  • G.M. Guisewite. 12. Trajectory Methods in Global Optimization
  • I. Diener. 13. Interval Methods
  • H. Ratschek, J. Rohne. 14. Stochastic Methods
  • C. Guus, E. Boender, H.E. Romeijn. Index.
巻冊次

v. 2 ISBN 9781402006326

内容説明

In 1995 the Handbook of Global Optimization (first volume), edited by R. Horst, and P.M. Pardalos, was published. This second volume of the Handbook of Global Optimization is comprised of chapters dealing with modern approaches to global optimization, including different types of heuristics. Topics covered in the handbook include various metaheuristics, such as simulated annealing, genetic algorithms, neural networks, taboo search, shake-and-bake methods, and deformation methods. In addition, the book contains chapters on new exact stochastic and deterministic approaches to continuous and mixed-integer global optimization, such as stochastic adaptive search, two-phase methods, branch-and-bound methods with new relaxation and branching strategies, algorithms based on local optimization, and dynamical search. Finally, the book contains chapters on experimental analysis of algorithms and software, test problems, and applications.

目次

  • Preface. 1. Tight relaxations for nonconvex optimization problems using the Reformulation-Linearization/Convexification Technique (RLT)
  • H.D. Sherali. 2. Exact algorithms for global optimization of mixed-integer nonlinear programs
  • M. Tawarmalani, N.V. Sahinidis. 3. Algorithms for global optimization and discrete problems based on methods for local optimization
  • W. Murray, Kien-Ming Ng. 4. An introduction to dynamical search
  • L. Pronzato, et al. 5. Two-phase methods for global optimization
  • F. Schoen. 6. Simulated annealing algorithms for continuous global optimization
  • M. Locatelli. 7. Stochastic Adaptive Search
  • G.R. Wood, Z.B. Zabinsky. 8. Implementation of Stochastic Adaptive Search with Hit-and-Run as a generator
  • Z.B. Zabinsky, G.R. Wood. 9. Genetic algorithms
  • J.E. Smith. 10. Dataflow learning in coupled lattices: an application to artificial neural networks
  • J.C. Principe, et al. 11. Taboo Search: an approach to the multiple-minima problem for continuous functions
  • D. Cvijovic, J. Klinowski. 12. Recent advances in the direct methods of X-ray crystallography
  • H.A. Hauptman. 13. Deformation methods of global optimization in chemistry and physics
  • L. Piela. 14. Experimental analysis of algorithms
  • C.C. McGeoch. 15. Global optimization: software, test problems, and applications
  • J.D. Pinter.

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