Titlebook: Evolutionary Algorithms; The Role of Mutation William M. Spears Book 2000 Springer-Verlag Berlin Heidelberg 2000 Graph.Master Patient Index

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Introductionm solving systems. A variety of evolutionary computational models have been proposed and studied — all of which are referred to as evolutionary algorithms (EAs). EAs share a common conceptual base of simulating the evolution of individual structures via processes of selection and perturbation. These

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Backgroundmbination and mutation. Naturally, this task would be made easier if in fact it could be proven that either mutation or recombination were in some sense always superior to the other (e.g., an EA without recombination will always outperform an EA with recombination). After all, as Schwefel (1995) sta

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Survival and Construction Schema Theory for Recombinationion as an operator than can construct hyperplanes from lower-order hyperplanes. One interesting observation can be made by comparing the graphs for disruption in Chap. 3 to those for construction in Chap. 4 — namely, that the graphs are qualitatively related in the sense that if one recombination op

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A Construction Schema Theory for Mutation lower-order hyperplane .. and that the other parent is a member of another lower-order hyperplane ... That chapter concluded by computing the expected number of offspring ..[..] that reside in .. after recombination, and showed that this is a simple function of ..(..), the population homogeneity ..

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Schema Theory: Mutation versus Recombinationisruptive aspect and the constructive aspect. Disruption refers to the likelihood that a .th-order hyperplane .. will not survive either recombination or mutation. Construction refers to the likelihood that a .th-order hyperplane will be created, given that one parent is a member of a lower-order hy

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Other Static Characterizations of Mutation and Recombinationat they do not take into account the dynamic time evolution of an EA. However, there have been other static characterizations of recombination that have been explored in the literature (such as “exploratory power,” “positional bias,” and “distributional bias”). The point of this chapter is to extend

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