Multi-strategy enterprise development optimizer for numerical optimization and constrained problems.

ABSTRACT: Enterprise Development Optimizer (EDO) is a meta-heuristic algorithm inspired by the enterprise development process with strong global search capability. However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. In order to solve these challenges, this paper proposes a multi-strategy enterprise development optimizer called MSEDO based on basic EDO. A leader-based covariance learning strategy is proposed, aiming to strengthen the quality of search agents and alleviate the weak population diversity of the EDO algorithm in the later search stage through the

SUBMITTER: Cai X 

PROVIDER: S-EPMC11950178 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature