摘要: 与传统优化方法相比,进化计算具有内在的并行性和自组织、自适应、自学习等智能特征,它在许多领域显示出巨大优势并取得一定成功。研究Multi-Agent协同进化算法,集成现有算法中的几种优势策略,利用混合策略的思想结合具体问题设计算法,并以实例说明该算法的有效性。
关键词:
多智能体,
进化算法,
蚁群算法
Abstract: In comparison with traditional optimization methods, evolutionary computation due to its intrinsic parallelism and some intelligent properties, such as self-organizing, self-adaptation, and self-learning. Evolutionary computation has been successfully applied to many fields. This paper proposes a Multi-Agent co-evolutionary algorithm, designs a new hybrid algorithm by combining evolutionary algorithm with some field-special strategies, and proves their efficiency by several experiments.
Key words:
Multi-Agent,
evolutionary algorithm,
Ant Colony Algorithm(ACA)
中图分类号:
周铁军;李 阳. Multi-Agent协同进化算法研究[J]. 计算机工程, 2009, 35(13): 205-207.
ZHOU Tie-jun; LI Yang. Research on Multi-Agent Co-evolutionary Algorithm[J]. Computer Engineering, 2009, 35(13): 205-207.