Affiliations: [a]
School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China
| [b]
Department of Mechanical Engineering, S.V. National Institute of Technology, Ichchanath, Surat, Gujarat, India
Correspondence:
[*]
Corresponding author. Xiaobing Yu, School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China. E-mail: yuxb111@163.com.
Abstract: Jaya, a simple heuristic algorithm, has shown attractive features, especially parameter-free. However, the simple structure of Jaya algorithm may result in poor performances, to boost the performance, a multi-strategy Jaya (MJaya) algorithm based on multi-population has been proposed in this paper. Three strategies correspond to three groups of solutions. The first strategy based on the first population is to introduce an adaptive weight parameter to the position-updating equation to improve the local search. The second strategy is based on rank-based mutation to enhance the global search. The third strategy is to exploit around the best solution to reinforce the local search. Three strategies cooperate well during the evolution process. The experimental results based on CEC 2014 have proven that the proposed MJaya is superior compared with Jaya and its latest variants. Then, the proposed MJaya algorithm is used to solve three industrial problems and the results have shown that the proposed MJaya algorithm can also solve complex industrial applications effectively.
