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.

Introduction to cellular GAs.- Panmictic GAs: cGAs versus steady-state and generational GAs.- Structured GAs: cGAs versus distributed GAs.- Using the ratio concept to define efficient cGAs.- New models with dynamic population shape in cGAs.- Multi-objective cGAs.- Memetic cGAs.- Theory of convergence for cGAs.- cGAs versus other metaheuristics.- cGAs for discrete optimization.- cGAs for continuous optimization.- cGAs for the vehicle routing problem.- cGAs for MANETS (mobile ad-hoc networks).- Index.