Local Selection

摘要

Local selection (LS) is a very simple selection scheme in evolutionary algorithms. Individual fitnesses are compared to a fixed threshold, rather than to each other, to decide who gets to reproduce. LS, coupled with fitness functions stemming from the consumption of shared environmental resources, maintains diversity in a way similar to fitness sharing; however it is generally more efficient than fitness 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 chasses. This papers characterizes one broad class of problems in which LS consistently outperforms tournament selection.