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Evolutionary optimization / edited by Ruhul Sarker, Masoud Mohammadian, Xin Yao.
- Format:
- Book
- Series:
- International series in operations research & management science ; 48.
- International series in operations research & management science ; 48
- Language:
- English
- Subjects (All):
- Mathematical optimization.
- Operations research.
- Evolutionary programming (Computer science).
- Physical Description:
- 1 online resource (433 p.)
- Edition:
- 1st ed. 2002.
- Place of Publication:
- Boston : Kluwer Academic Publishers, c2002.
- Language Note:
- English
- Summary:
- Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.
- Contents:
- Conventional Optimization Techniques
- Evolutionary Computation
- Single Objective Optimization
- Evolutionary Algorithms and Constrained Optimization
- Constrained Evolutionary Optimization
- Multi-Objective Optimization
- Evolutionary Multi-Objective Optimization: A Critical Review
- Multi-Objective Evolutionary Algorithms for Engineering Shape Design
- Assessment Methodologies for Multiobjective Evolutionary Algorithms
- Hybrid Algorithms
- Utilizing Hybrid Genetic Algorithms
- Using Evolutionary Algorithms to Solve Problems by Combining Choices of Heuristics
- Constrained Genetic Algorithms and Their Applications in Nonlinear Constrained Optimization
- Parameter Selection in EAs
- Parameter Selection
- Application of EAs to Practical Problems
- Design of Production Facilities Using Evolutionary Computing
- Virtual Population and Acceleration Techniques for Evolutionary Power Flow Calculation in Power Systems
- Application of EAs to Theoretical Problems
- Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
- A Genetic Algorithm Heuristic for Finite Horizon Partially Observed Markov Decision Problems
- Using Genetic Algorithms to Find Good K-Tree Subgraphs.
- Notes:
- Description based upon print version of record.
- Includes bibliographical references and index.
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 1-280-46221-3
- 9786610462216
- 0-306-48041-7
- OCLC:
- 559313621
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