| 直觉模糊离散粒子群算法 |
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| 引用本文： | 汪禹喆,雷英杰,周 林,李润玲.直觉模糊离散粒子群算法[J].控制与决策,2012,27(11):1735-1739. |
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| 作者姓名： | 汪禹喆 雷英杰 周 林 李润玲 |
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| 作者单位： | 空军工程大学导弹学院;北京军代局232厂 |
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| 基金项目： | 国家自然科学基金项目(60773209);陕西省自然科学基金项目(2006F18) |
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| 摘 要： | 在研究和分析离散粒子群算法(DBPSO)的基础上,提出一种基于直觉模糊熵的改进离散粒子群算法(IFDPSO).该算法以直觉模糊熵作为粒子群状态测度和速度变异的基本参数,同时加入了位置变异策略以保证算法在有限时间内尽可能多地遍历到次优位置及其邻域,增强了算法的全局寻优能力.实验数据表明,在求解较大规模整数规划问题(如0-1背包问题)时,IFDPSO比DPSO和蚁群算法(ACO)更为有效,从而为解决这类问题提供了新的途径和方法.
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| 关 键 词： | 离散粒子群算法 直觉模糊熵 直觉模糊离散粒子群算法 背包问题 |
| 收稿时间： | 2011/4/28 0:00:00 |
| 修稿时间： | 2011/9/1 0:00:00 |
Intuitionistic fuzzy discrete particle swarm algorithm |
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| WANG Yu-zhe,LEI Ying-jie,ZHOU Lin,LI Run-ling.Intuitionistic fuzzy discrete particle swarm algorithm[J].Control and Decision,2012,27(11):1735-1739. |
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| Authors: | WANG Yu-zhe LEI Ying-jie ZHOU Lin LI Run-ling |
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| Affiliation: | 1.Missile Institute,Air Force Engineering University,Sanyuan 713800,China;2.Air Force Agency Office of 232 Factory in Beijing,Beijing 100000,China.) |
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| Abstract: | On the basis of the analysis and research on discrete particle swarm optimization algorithm(DPSO), an improved
DPSO algorithm(IFDPSO) based on intuitionistic fuzzy entropy is proposed, which takes the intuitionistic fuzzy entropy
as the measure of the state of particle swarm and the parameter of velocity mutation. With the location mutation strategy,
the IFDPSO can possibly search as much as possible sub-optimal location and its neighborhood, and the algorithm ability
of searching global best value is intensified. The experimental data shows that, in solving large scale integer programming
problem such as 0-1 knapsack problem, IFDPSO algorithm represents more effective than DPSO algorithm and ant colony
optimization(ACO) algorithm, which provides a new way for solving 0-1 knapsack problem. |
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