Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Dec. 21, 2023

The grey wolf optimizer is an effective and well-known meta-heuristic algorithm, but it also has the weaknesses of insufficient population diversity, falling into local optimal solutions easily, unsatisfactory convergence speed. Therefore, we propose a hybrid (HGWO), based mainly on exploitation phase harris hawk optimization. It includes initialization with Latin hypercube sampling, nonlinear factor perturbations, some extended exploration strategies. In HGWO, wolves can have hawks-like flight capabilities during position updates, which greatly expands search range improves global searchability. By incorporating greedy will relocate only if new location superior to current one. This paper assesses performance (HGWO) by comparing other heuristic algorithms enhanced schemes optimizer. evaluation conducted using 23 classical benchmark test functions CEC2020. experimental results reveal that HGWO algorithm performs well in terms its ability, speed, accuracy. Additionally, demonstrates considerable advantages solving engineering problems, thus substantiating effectiveness applicability.

Language: Английский