A New Look at Solving Minimax Problems with Coevolutionary Genetic Algorithms
In recent work coevolutionary algorithms have been used to solve minimax problems from mechanical structure optimization and scheduling domains. The applications have been quite successful, but the algorithms used require the search-space of the minimax problem to have a certain symmetric property. The present article argues that the proposed algorithms will fail to converge if the problem does not have the symmetric property. The difficulty is demonstrated to come from the fitness evaluation of the previous algorithms, and a new kind of fitness evaluation for minimax problems is proposed. Experiments reveal that an algorithm using the new fitness evaluation clearly outperforms the previously proposed algorithms.
KeywordsMinimax problems Coevolution Optimization.
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