Iterative Computer Algorithms with Applications in Engineering Solving Combinatorial Optimization Problems

Name: Iterative Computer Algorithms with Applications in Engineering Solving Combinatorial Optimization Problems
Availability: InStock
ISBN: 9780769501000

ISBN-10: 0769501001

ISBN-13: 9780769501000

Edition: 1999

Authors: Sadiq M. Sait, Habib Youssef

List price: $149.95

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Book details

List price: $149.95
Copyright year: 1999
Publisher: John Wiley & Sons, Incorporated
Publication date: 2/10/2000
Binding: Paperback
Pages: 416
Size: 5.98" wide x 9.07" long x 1.01" tall
Weight: 1.606
Language: English



Preface



Introduction



Combinatorial Optimization



Optimization Methods



States, Moves, and Optimality



Local Search



Optimal versus Final Solution



Single versus Multicriteria Constrained Optimization



Convergence Analysis of Iterative Algorithms



Markov Chains



Parallel Processing



Summary and Organization of the Book


References


Exercises



Simulated Annealing (SA)



Introduction



Simulated Annealing Algorithm



SA Convergence Aspects



Parameters of the SA Algorithm



SA Requirements



SA Applications



Parallelization of SA



Conclusions and Recent Work


References


Exercises



Genetic Algorithms (GAs)



Introduction



Genetic Algorithm



Schema Theorem and Implicit Parallelism



GA Convergence Aspects



GA in Practice



Parameters of GAs



Applications of GAs



Parallelization of GA



Other Issues and Recent Work



Conclusions


References


Exercises



Tabu Search (TS)



Introduction



Tabu Search Algorithm



Implementation-Related Issues



Limitations of Short-Term Memory



Examples of Diversifying Search



TS Convergence Aspects



TS Applications



Parallelization of TS



Other Issues and Related Work



Conclusions


References


Exercises



Simulated Evolution (SimE)



Introduction



Historical Background



Simulated Evolution Algorithm



SimE Operators and Parameters



Comparison of SimE, SA, and GA



SimE Convergence Aspects



SimE Applications



Parallelization of SimE



Conclusions and Recent Work


References


Exercises



Stochastic Evolution (StocE)



Introduction



Historical Background



Stochastic Evolution Algorithm



Stochastic Evolution Convergence Aspects



Stochastic Evolution Applications



Parallelization of Stochastic Evolution



Conclusions and Recent Work


References


Exercises



Hybrids and Other Issues



Introduction



Overview of Algorithms



Hybridization



GA and Multiobjective Optimization



Fuzzy Logic for Multiobjective Optimization



Artificial Neural Networks



Quality of the Solution



Conclusions


References


Exercises


About the Authors


Index