QR Mutations Improve Many Evolution Strategies: A Lot On Highly Multimodal Problems

Previous studies have shown the efficiency of using quasi- random mutations on the well-know CMA evolution strategy. Quasi-random mutations have many advantages, in particular their application is stable, efficient and easy to use. In this article, we extend this principle by applying quasi-random mutations on several well known continuous evolutionary algorithms (SA, CMSA, CMA) and do it on several old and new test functions, and with several criteria. The results point out a clear improvement compared to the baseline, in all cases, and in particular for moderate computational budget.

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