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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.

Economics/Management Science. --- Mathematical Modeling and Industrial Mathematics. --- Optimization. --- Production/Logistics. --- Algorithms. --- Genetics and Population Dynamics. --- Operations Research/Decision Theory. --- Economics. --- Genetics --- Mathematical optimization. --- Business logistics. --- Economie politique --- Algorithmes --- Optimisation mathématique --- Logistique (Organisation) --- Mathematics. --- Genetic algorithms. --- Nonlinear programming. --- Operations Research --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Evolutionary programming (Computer science) --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Production management. --- Operations research. --- Decision making. --- Numerical analysis. --- Biomathematics. --- Numerical Analysis. --- Operation Research/Decision Theory. --- Operations Management. --- Programming (Mathematics) --- Algorithms --- Combinatorial optimization --- Evolutionary computation --- Genetic programming (Computer science) --- Learning classifier systems --- Computer programming --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Manufacturing management --- Industrial management --- Algorism --- Algebra --- Arithmetic --- Biology --- Embryology --- Mendel's law --- Adaptation (Biology) --- Breeding --- Chromosomes --- Heredity --- Mutation (Biology) --- Variation (Biology) --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Foundations --- Mathematics --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Decision making --- Population genetics. --- Operations Research and Decision Theory. --- Population Genetics.