Application of spiral enhanced whale optimization algorithm in solving optimization problems.

ABSTRACT: The Whale Optimization Algorithm (WOA) is regarded as a classic metaheuristic algorithm, yet it suffers from limited population diversity, imbalance between exploitation and exploration, and low solution accuracy. In this paper, we propose the Spiral-Enhanced Whale Optimization Algorithm (SEWOA), which incorporates a nonlinear time-varying self-adaptive perturbation strategy and an Archimedean spiral structure into the original WOA. The Archimedean spiral structure enhances the diversity of the solution space, aiding the algorithm in escaping local optima. The nonlinear time-varying self-adaptive optimization dynamic perturbation strategy improves the algorithm's local search capability and enhances solution accuracy. The effectiveness of the proposed algorithm is validated from multiple p

SUBMITTER: Qu S 

PROVIDER: S-EPMC11489690 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature