Multiple Cyclic Swarming Optimization
for Uni- and Multi-modal Functions

Faculty	Science	Year:	2020
Type of Publication:	ZU Hosted	Pages:	887-898
Authors:	Staff Zu Site Abstract In Staff Site
Journal:	1087 Springer	Volume:

Keywords :	Multiple Cyclic Swarming Optimization for Uni- , Multi-modal
Abstract:	This paper proposed multiple cyclic exploration and exploitation at two levels on the basis of improved whale swarming and particle swarm optimization algorithms. The first level covers exploration, and different subsets of candidate solutions are used to explore the search space, while the second level covers exploitation. The whale optimization algorithm (WOA) was used at the first level and the particle swarm optimization (PSO) at the second level. The proposed approach is tested on twenty benchmark test functions, and initiatory results are presented. According to the computational results, the proposed approach more successful of the state-ofthe-art algorithms.

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