Competitive Evolution: A Natural Approach to Operator Selection

One of the main problems in applying evolutionary optimisation methods is the choice of operators and parameter values. This paper propose a competitive evolution method, in which several subpopulations are allowed to compete for computer time. The population with the fittest members, and that with the highest improvement rate in the recent past, are rewarded. When using identical strategies in the subpopulations, this competitive strategy provides an insurance against unlucky runs while extracting only an insignificant cost in terms of extra function evaluations. When using different strategies in the subpopulations, it ensures that the best strategies are used and again the extra cost is not great. Competitive evolution is at its best when an operator - or the lack of it - may have a very detrimental effect which is not known in advance. Occasional mixing of the best performing subpopulations leads to further improvement. Symbols d normalised distance between two vectors x (equation ...

• Type: Conference
• Year: 1994
• Where: EVOW
• Authors: Q. Tuan Pham
• Keywords: Allowable Value, Artificial Intelligence, Competitive Evolution, EVOW 1994, Mutation Frequency