Attraction basin sphere estimation approach for niching CMA-ES

Abstract

Many real-world problems are multimodal, which means algorithms should have the ability to find all or most of the multiple solutions as opposed to a single best solution. Niching is the technique that can help evolutionary algorithms to find multiple solutions. Attraction basin sphere estimation (ABSE) is a newly proposed niching method which has the power of inferring the shape of fitness landscapes by spending some extra evaluations. However, when we apply ABSE to genetic algorithms, those extra evaluations lead to an efficiency problem. However, we notice that the combination of ABSE and covariance matrix adaptation evolution strategy will not cause the efficiency problem and have a good performance. This paper implements this idea and performs experiments on a benchmark set provided by CEC 2013 niching methods competition. The algorithm is compared with the best 5 algorithms in the competition. The results show that the proposed algorithm obtains a good result. The features of the proposed algorithm are also discussed in detail.