Abstract

Grey wolf optimizer (GWO) algorithm is a newly proposed swarm-intelligence based algorithm. GWO is used to solve various complex optimization issues in distinct fields. Several researchers have endeavored to increase GWO performance by implementing some modifications. This work aims to introduce a prey phase in GWO to enhance exploration in the initial search process. The proposed prey phase GWO (PGWO) is evaluated on several benchmark optimization functions. The results of PGWO is compared with GWO and PSO. The proposed algorithm has shown better results as compared to GWO and PSO.

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