Evolutionary Computation 1 Basic Algorithms and Operators

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

WHY EVOLUTIONARY COMPUTATION?Introduction to evolutionary computation Possible applications of evolutionary computation Advantages (and disadvantages) of evolutionary computation over other approachesEVOLUTIONARY COMPUTATION: THE BACKGROUNDPrinciples of evolutionary processesPrinciples of geneticsA history of evolutionary computationEVOLUTIONARY ALGORITHMS AND THEIR STANDARD INSTANCESIntroduction to evolutionary algorithmsGenetic algorithmsEvolution strategiesEvolutionary programmingDerivative methods in genetic programmingLearning classifier systemsHybrid methods REPRESENTATIONSIntroduction to representationsBinary stringsReal-valued vectorsPermutationsFinite-state representationsParse treesGuidelines for a suitable encodingOther representations SELECTIONIntroduction to selectionProportionary selection and sampling algorithmsTournament selectionRank-based selectionBoltzmann selectionOther selection methodsGeneration gap methodsA comparison of selection mechanismsInteractive evolution SEARCH OPERATORSIntroduction to search operatorsMutation operatorsRecombinationOther operatorsINDEX