元启发优化算法综述

王 天宝
天津商业大学宝德学院 300384

摘要

元启发优化算法受自然现象和生物行为启发，适用于解决复杂优化问题。根据算法的启发源分为基于群体智能、进化、生物行为与人类智能、物理原理以及数学方法五类，并强调了其平衡、记忆、自适应和并行寻优的特点。介绍了近两年提出的创新算法，探讨了通过混沌映射和随机扰动等策略来提升算法性能，展望了算法理论研究、通用性和适应性、效率提升以及跨学科融合等未来发展方向。

关键词

元启发；群体优化;技能优化算法;混沌映射；高斯变异

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