Cellular Genetic Algorithms

Bernabe Dorronsoro, Enrique Alba (auth.)0387776095, 978-0-387-77609-5, 978-0-387-77610-1, 0387776109

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. This class of genetic algorithms is shown to produce impressive results on a whole range of domains, including complex problems that are epistatic, multi-modal, deceptive, discrete, continuous, multi-objective, and random in nature. The focus of this book is twofold. On the one hand, the authors present new algorithmic models and extensions to the basic class of Cellular GAs in order to tackle complex problems more efficiently. On the other hand, practical real world tasks are successfully faced by applying Cellular GA methodologies to produce workable solutions of real-world applications. These methods can include local search (memetic algorithms), cooperation, parallelism, multi-objective, estimations of distributions, and self-adaptive ideas to extend their applicability.

The methods are benchmarked against well-known metaheutistics like Genetic Algorithms, Tabu Search, heterogeneous GAs, Estimation of Distribution Algorithms, etc. Also, a publicly available software tool is offered to reduce the learning curve in applying these techniques. The three final chapters will use the classic problem of “vehicle routing” and the hot topics of “ad-hoc mobile networks” and “DNA genome sequencing” to clearly illustrate and demonstrate the power and utility of these algorithms.

Table of contents :
Front Matter….Pages 1-12
Front Matter….Pages 1-1
Introduction to Cellular Genetic Algorithms….Pages 3-20
The State of the Art in Cellular Evolutionary Algorithms….Pages 21-34
Front Matter….Pages 1-1
On the Effects of Structuring the Population….Pages 37-46
Some Theory: A Selection Pressure Study on cGAs….Pages 47-69
Front Matter….Pages 1-1
Algorithmic and Experimental Design….Pages 73-82
Design of Self-adaptive cGAs….Pages 83-99
Design of Cellular Memetic Algorithms….Pages 101-114
Design of Parallel Cellular Genetic Algorithms….Pages 115-126
Designing Cellular Genetic Algorithms for Multi-objective Optimization….Pages 127-138
Other Cellular Models….Pages 139-152
Software for cGAs: The JCell Framework….Pages 153-163
Front Matter….Pages 1-1
Continuous Optimization….Pages 167-174
Logistics: The Vehicle Routing Problem….Pages 175-186
Telecommunications: Optimization of the Broadcasting Process in MANETs….Pages 187-202
Bioinformatics: The DNA Fragment Assembly Problem….Pages 203-210
Back Matter….Pages 1-35