具有自适应多子群的海洋捕食者算法新策略

New Strategy for Marine Predator Algorithm with Adaptive Multi-subpopulation

基于多子群海洋捕食者算法提出在探索与开发阶段动态地采用新系数,并针对追随者子群更新算法进行优化.通过自适应调整领导者子群、追随者子群和衔尾者子群的种群规模,在全局探索和局部开发需求之间取得平衡.采用多种算法进行对比试验,结果表明该策略在优化问题上取得了改进和成效,适用性更广,为后续的研究和应用提供了重要的参考与借鉴.

This paper proposes a new strategy based on the multi-subpopulation marine predator algorithm.The proposed approach employs new coefficients dynamically during the exploration and exploitation stages,and optimizes the update algorithm for the follower subpopulation.Furthermore,by adaptively adjusting the population sizes of leader,follower,and trailer subpopulations,a better balance between global exploration and local exploitation needs is achieved.Comparative experiments with various algorithms have been conducted,and the results demonstrate that the new strategy has achieved significant improvement and effectiveness in optimization problems,broadening its applicability and providing important references and insights for subsequent research and applications.