New Approaches to Coevolutionary Worst-Case Optimization

Authors:
Jürgen Branke;Johanna Rosenbusch
Affiliations:
Institute AIFB, University of Karlsruhe, Germany;Institute AIFB, University of Karlsruhe, Germany
Venue:
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Year:
2008

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Abstract

Many real-world optimization problems involve uncertainty. In this paper, we consider the case of worst-case optimization, i.e., the user is interested in a solution's performance in the worst case only. If the number of possible scenarios is large, it is an optimization problem by itself to determine a solution's worst case performance. In this paper, we apply coevolutionary algorithms to co-evolve the worst case test cases along with the solution candidates. We propose a number of new variants of coevolutionary algorithms, and show that these techniques outperform previously proposed coevolutionary worst-case optimizers on some simple test problems.