基于改进的蜂群遗传算法求解多选择背包问题
多选择背包问题是组合优化中的典型NP难题之一。针对传统蜂群算法存在的收敛速度慢、易陷入局部最优的缺点，提出改进策略。改进的算法通过设置两个自适应变化的种群雄蜂群和雌蜂群，雄蜂群负责与蜂后交叉操作以保持种群的选择压力，雌蜂群负责自适应变异操作以保持种群多样性，蜂后则根据启发式规则主动进化以局部寻优。根据算法实现的核心思想，仿真实验结果表明，提出的改进算法可以有效避免陷入局部最优，同时通过实例也验证了算法的可行性和有效性。...
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| Published in | 计算机应用研究 Vol. 31; no. 6; pp. 1632 - 1634 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
齐齐哈尔大学计算机与控制工程学院,黑龙江齐齐哈尔,161006%武汉理工大学信息工程学院,武汉,430070
2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2014.06.006 |
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| Summary: | 多选择背包问题是组合优化中的典型NP难题之一。针对传统蜂群算法存在的收敛速度慢、易陷入局部最优的缺点，提出改进策略。改进的算法通过设置两个自适应变化的种群雄蜂群和雌蜂群，雄蜂群负责与蜂后交叉操作以保持种群的选择压力，雌蜂群负责自适应变异操作以保持种群多样性，蜂后则根据启发式规则主动进化以局部寻优。根据算法实现的核心思想，仿真实验结果表明，提出的改进算法可以有效避免陷入局部最优，同时通过实例也验证了算法的可行性和有效性。 |
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| Bibliography: | 51-1196/TP WU Di（School of Computer ＆ Control Engineering, Qiqihaer University, Qiqihaer Heilongjiang 161006, China） YANG Xin-yu（School of Computer ＆ Control Engineering, Qiqihaer University, Qiqihaer Heilongjiang 161006, China） WANG Chong（School of Computer ＆ Control Engineering, Qiqihaer University, Qiqihaer Heilongjiang 161006, China） LI Wei-ping（College of Information Engineering, Wuhan University of Technology , Wuhan 430070, China） Multiple-choice knapsack problem （MCKP） is NP hard as one of combinatorial optimization. This paper proposed a bee-swarm genetic algorithm （BSGA） to solve MCKP. There were two adaptive populations in BSGA, male bee swarm cross- overed with queen to keep pressure of selection, female swarm mutated to keep population diversity, the queen evolved under the instruction of heuristic rules. It presented the main idea of BSGA and implemented by MATLAB. Through a kind of instances, BSGA compared with other algorithms ,it shows the feasibility and effectiveness of the proposed algorithm |
| ISSN: | 1001-3695 |
| DOI: | 10.3969/j.issn.1001-3695.2014.06.006 |