Genetic algorithms in engineering and computer science
著者
書誌事項
Genetic algorithms in engineering and computer science
Wiley, c1995
大学図書館所蔵 全42件
注記
Includes bibliographies
内容説明・目次
内容説明
This study describes evolution-based algorithms used for both the study of complex systems and the resolution of difficult optimization problems. Evolution algorithms are techniques drawn from artificial intelligence which mimic nature according to Darwin's principle of the survival of the fittest. The contributors describe theoretical, numerical and applied aspects of genetic algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems. They link artificial intelligence and scientific computing in order to increase the performance of evolution programs for solving real problems.
目次
- Partial table of contents:
- THEORETICAL AND COMPUTATIONAL ASPECTS IN GAs AND ESs
- Evolving Multi-Agent Systems (T. Fogarty, et al.)
- The Existential Pleasures of Genetic Algorithms (D. Goldberg)
- A General Study on Genetic Fuzzy Systems (O. Cordsn and F. Herrera)
- The Science of Breeding and Its Application to Genetic Algorithms (H. M
- hlenbein)
- Modeling Hybrid Genetic Algorithms (D. Whitley)
- APPLICATIONS AND COMPUTATIONAL IMPLEMENTATION
- Parallel genetic Algorithms for Optimization in CFD (D. Doorly)
- Genetic Algorithm Modules in MATLAB: Design and Implementation using Software Engineering Practices (A. Satyadas and K. Krishnakumar)
- Hybrid GA for Multi Objective Aerodynamic Shape Optimization (C. Poloni)
- Genetic Algorithms Applications in Computational Fluid Dynamics (D. Quagliarella).
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