| 多目标0-1规划问题的蜂群算法 |
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| 引用本文： | 韩燕燕,马良,赵小强.多目标0-1规划问题的蜂群算法[J].运筹与管理,2012,21(2):23-26. |
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| 作者姓名： | 韩燕燕 马良 赵小强 |
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| 作者单位： | 1. 上海理工大学管理学院 上海200093
2. 北京市昌平区66391部队 北京102205 |
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| 基金项目： | 国家自然科学基金资助项目，上海市重点学科建设项目资助 |
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| 摘 要： | 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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| 关 键 词： | 智能优化 组合优化 蜂群算法 多目标0-1规划问题 |
Bee Colony Algorithm for the Multi-objective 0-1 Programming Problem |
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| HAN Yan-yan
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MA Liang
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ZHAO Xiao-qiang.Bee Colony Algorithm for the Multi-objective 0-1 Programming Problem[J].Operations Research and Management Science,2012,21(2):23-26. |
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| Authors: | HAN Yan-yan MA Liang ZHAO Xiao-qiang |
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| Institution: | 1.School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China;2.66391 Troop,Changping District of Beijing,Beijing 102205,China) |
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| Abstract: | 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. |
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| Keywords: | intelligent optimization combinatorial optimization bee colony algorithm multi-objective 0-1 programming problem |
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