关键词: 二元蚁群, 多种群, 环境评价, 混合行为, 多目标

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.

Key words: binary ant colony algorithm, multi-population, environmental evaluation, concrete behaviors, multi-objective