An improved enterprise development optimizer based on labor migration for numerical optimization.

ABSTRACT: Enterprise Development Optimizer (EDO) is a meta-heuristic algorithm inspired by the enterprise development process. Although EDO is effective in the optimization field, it suffers from issues such as premature convergence and unequal exploration-exploitation ratio. These shortcomings restrict the performance of the algorithm in some complex problem. This research proposes an improved EDO, called LMEDO, in which EDO is integrated with incorporates time-phase based switching strategy, economy-driven guided based learning strategy and spatial selectivity-based selection strategy to improve convergence rate, stability, and search effectiveness. Among these strategies, the time-phase based switching strategy allows EDO to better apply different search strategies and enhances the search capabil

SUBMITTER: Zhao D 

PROVIDER: S-EPMC12276289 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature