计算机工程与应用2011，Vol.47Issue(17)：37-41,5.DOI:10.3778/j.issn.1002-8331.2011.17.011
多目标优化的多种群混合行为二元蚁群算法
Multi-population binary ant colony algorithm with concrete behaviors for multi-objective optimization problem
摘要
Abstract
Aiming at solving the drawbacks of the original binary ant colony algorithm on multi-objective optimization problems:easy to fall into the local optimization and difficult to get the Pareto optimal solutions,Multi-Population Binary Ant colony algorithm with Concrete Behaviors(MPBACB) is proposed.This algorithm introduces multi-population method to ensure the global optimization ability, and uses environmental evaluation/reward model to improve the searching efficiency.Furthermore, concrete ant behaviors are defined to stabilize the performance of the algorithm.Experimental results on several constrained multi-objective functions prove that the algorithm ensures the good global search ability,and has better effect on the multi-objective problems.关键词
二元蚁群/多种群/环境评价/混合行为/多目标Key words
binary ant colony algorithm/multi-population/ environmental evaluation/ concrete behaviors/multi-objective分类
信息技术与安全科学引用本文复制引用
叶青,熊伟清,李纲..多目标优化的多种群混合行为二元蚁群算法[J].计算机工程与应用,2011,47(17):37-41,5.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60472099) （the National Natural Science Foundation of China under Grant No.60472099）
浙江省自然科学基金(No.Y1080363) （No.Y1080363）
宁波市自然科学基金(No.2007A610051). （No.2007A610051）
