Cellular genetic algorithms
Author(s)
Bibliographic Information
Cellular genetic algorithms
（Operations research/computer science interface series, 42）
Springer, c2008
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Note
Includes bibliographical references (p. [225]-242) and index
Description and Table of Contents
Description
Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice. This book is a key source for studying and designing cellular GAs, as well as a self-contained primary reference book for these algorithms.
Table of Contents
I Introduction.- to Cellular Genetic Algorithms.- The State of the Art in Cellular Evolutionary Algorithms.- II Characterizing Cellular Genetic Algorithms.- On the Effects of Structuring the Population.- Some Theory: A Selection Pressure Study on cGAs.- III Algorithmic Models and Extensions.- Algorithmic and Experimental Design.- Design of Self-adaptive cGAs.- Design of Cellular Memetic Algorithms.- Design of Parallel Cellular Genetic Algorithms.- Designing Cellular Genetic Algorithms for Multi-objective Optimization.- Other Cellular Models.- Software for cGAs: The JCell Framework.- IV Applications of cGAs.- Continuous Optimization.- Logistics: The Vehicle Routing Problem.- Telecommunications: Optimization of the Broadcasting Process in MANETs.- Bioinformatics: The DNA Fragment Assembly Problem.
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