A Hybrid Salp Swarm Algorithm With Gravitational Search Mechanism
Sheng Li, Yang Yu, Daiki Sugiyama, Qianqian Li, Shangce Gao · 2018
The paper presents a hybrid approach which combines salp swarm algorithm (SSA) with gravitational search algorithm (GSA). SSA is a newly proposed meta-heuristic algorithm and can obtain good results in solving some optimization problems. However, its performance is still raw, especially in dealing with complex problems. Thus, in this paper, we introduce a powerful algorithm GSA which has considerable capacity to enhance the search ability of SSA. The proposed algorithm is tested by CEC'17 benchmark functions and the result indicates that this hybridization has considerable merits in terms of solution accuracy and convergence speed.