The Chaotic Slime Mould Algorithm with Chebyshev Map
Juan Zhao, Zheng-Ming Gao
Abstract
Abstract In this paper, we proposed an improvement for the newly raised swarm-based algorithm called the slime mould algorithm (SMA) with chaos. The so-called chaotic SMA introduced the specific Chebyshev mapping, which had already been verified to perform better in optimization. Three types of simulation experiments were carried out with the unimodal, multi-modal benchmark functions and those which have basins/valleys in their profiles. In order to reduce the influence of randomness involved in the algorithms, 100 Monte Carlo experiments were carried out and the final results were their averages. Results confirmed the capability of the improvements and demonstrated that the chaotic SMA with Chebyshev map would perform better, steadier, and faster than the original one in optimization. Discussions on the capability in optimization of the chaotic SMA together with the original SMA were made, and the chaotic SMA was recommended in applications for real engineering problems.