In order to solve the multi-objective 0-1 programming problem with linear constrains, we present a new intelligent optimization algorithm--bee colony algorithm. The algorithm is coded and implemented on microcomputer through aseries of numerical tests. Comparisons with genetic algorithm, ant colony optimization algorithm and cellular ant colony algorithm show that the bee colony algorithm can get more pareto solutions to the multi-objective 0-1 programming problem. And the effectiveness of the Bee Colony Algorithm is validated.%针对多目标0-1规划问题,本文给出一种新型的智能优化算法——蜂群算法进行求解,并通过实例验证,与遗传算法、蚁群算法和元胞蚁群算法作了相应比较.就多目标0-1规划问题而言,蜂群算法能得到更多的Pareto解,说明了蜂群算法在解决该类问题上的有效性.
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