作者
Marziyeh Dadvar, Hamidreza Navidi, Hamid Haj Seyyed Javadi, Mitra Mirzarezaee
发表日期
2022/3
期刊
Applied Intelligence
卷号
52
期号
4
页码范围
4089-4108
出版商
Springer US
简介
The present paper proposes a new algorithm designed for solving optimization problems. This algorithm is a hybrid of Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. The proposed algorithm uses a coalition or cooperation model in the game theory to combine the DE and PSO algorithms. This is done in an attempt to keep a balance between the exploration and exploitation capabilities by preventing population stagnation and avoiding the local optimum. The DE and PSO algorithms are two players in the state space, which play cooperative games together using the Nash bargaining theory to find the best solution. To evaluate the performance of the proposed algorithm, 25 benchmark functions are used in terms of the CEC2005 structure. The proposed algorithm is then compared with the classical DE and PSO algorithms and the hybrid algorithms recently proposed. The results …
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