Bee Spices Transition with Rapid Global Optimization Algorithm

XU-MING HAN, LIN-LIN WANG, LI ZHENG, YUAN-YUAN DANG, LI-MIN WANG

Abstract


Swarm intelligence algorithm is a general term for a class of intelligent groups with self-organized behavior. A novel Artificial Bee Colony algorithm is introduced in this paper, named Bee Spices Transition with Rapid Global Optimization Algorithm (BSTRGOA). The contribution of BSTRGOA algorithm consists of two parts. First, the evolution strategy of bee species balances the global exploration ability and the local search ability. Second, the fast search mechanism of global optimization is proposed. It reinforces global learning of the colony. The BSTRGOA algorithm is experimented with the CEC 2017 benchmark functions. It shows the BSTRGOA algorithm can effectively improve the convergence speed and optimization accuracy. And the BSTRGOA algorithm has a good performance in solving the problem of multi-dimensional function optimization. In addition, BSTRGOA algorithm is also applicable to dynamic economic scheduling analysis, and the conclusion also shows it can significantly improve the time efficiency.

Keywords


Bee spices transition, Function optimization, Meta heuristic, Artificial bee colony, Dynamic economic dispatch.Text


DOI
10.12783/dtcse/cmso2019/33604

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