Local Selection

Local selection (LS) is a very simple selection scheme in evolutionary algorithms. Individual tnesses are compared to a xed threshold , rather than to each other, to decide who gets to reproduce. LS, coupled with tness functions stemming from the consumption of shared environmental resources, maintains diversity in a way similar to tness sharing; however it is generally more eecient than tness sharing, and lends itself to parallel implementations for distributed tasks. While LS is not prone to premature convergence, it applies minimal selection pressure upon the population. LS is therefore more appropriate than other, stronger selection schemes only on certain problem classes. This papers characterizes one broad class of problems in which LS consistently out-performs tournament selection.

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