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Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness evaluation, constraint-handling techniques, population structures, advanced techniques in evolutionary computation, and the implementation of evolutionary algorithms. It is intended to be used by individual researchers and students in the expanding field of evolutionary computation.
FITNESS EVALUATIONIntroduction to fitness evaluationEncoding and decoding functionsCompetitive fitness evaluationComplexity-based fitness evaluationMultiobjective optimizationCONSTRAINT-HANDLING TECHNIQUESIntroduction to constraint-handling techniquesPenalty functionsDecodersRepair algorithmsConstraint-preserving operatorsOther constraint-handling methodsConstraint-satisfaction problemsPOPULATION STRUCTURESNiching methodsSpeciation methodsIsland (migration) models: evolutionary algorithms based on punctuated equilibriaDiffusion (cellular) modelsADVANCED TECHNIQUES IN EVOLUTIONARY COMPUTATIONPopulation sizingMutation parametersRecombination parametersParameter controlSelf-adaptationMeta-evolutionary approachesCoevolutionary algorithmsIMPLEMENTATION OF EVOLUTIONARY ALGORITHMSEfficient implementation of algorithmsComputation time of evolutionary operatorsHardware realizations of evolutionary algorithmsINDEX
"This second volume provides very interesting information and updated material on additional topics. It also covers some advanced techniques and discusses the efficient implementation of evolutionary algorithms."-H.D. Hecker, Zentralblatt Math