| 解多目标约束问题的改进MaxMin-PSO算法 |
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| 引用本文： | 黄圣杰,罗琦,佟金颖. 解多目标约束问题的改进MaxMin-PSO算法[J]. 计算机工程与应用, 2008, 44(15): 48-50. DOI: 10.3778/j.issn.1002-8331.2008.15.014 |
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| 作者姓名： | 黄圣杰 罗琦 佟金颖 |
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| 作者单位： | 南京信息工程大学,信息与控制学院,南京,210044;南京信息工程大学,信息与控制学院,南京,210044;南京信息工程大学,信息与控制学院,南京,210044 |
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| 摘 要： | 将最大最小化适应度函数与罚函数相结合，提出了一种实用有效求解多目标约束优化问题的粒子群算法。采用归类和比较的思想进行替换非劣解；改变以往全局最优值的选取方法，而采用轮序方式从非劣解中获取。实验证明改进的MaxMin-PSO算法能更加有效的逼近Pareto解，收敛速度更快，分布更均匀，且能很好的抑制低维多目标约束问题的发散现象。
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| 关 键 词： | 粒子群算法 最大最小适应函数 轮序 罚函数 |
| 文章编号： | 1002-8331(2008)15-0048-03 |
| 收稿时间： | 2007-09-04 |
| 修稿时间： | 2007-09-04 |
Improved MaxMin Particle Swarm Optimization for solving multiobjective constrained optimization problems |
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| HUANG Sheng-jie,LUO Qi,TONG Jin-ying. Improved MaxMin Particle Swarm Optimization for solving multiobjective constrained optimization problems[J]. Computer Engineering and Applications, 2008, 44(15): 48-50. DOI: 10.3778/j.issn.1002-8331.2008.15.014 |
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| Authors: | HUANG Sheng-jie LUO Qi TONG Jin-ying |
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| Affiliation: | Department of Information and Communication，Nanjing University of Science and Technology，Nanjing 210044，China |
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| Abstract: | In this paper,Max-Min fitness function and penalty function are combined together,and a practical and effective particle swarm optimization algorithm is proposed to solve multi-objectives constrained optimization problems.Non-inferior solutions are replaced according to the idea of cluster and compare.The method of selecting globally optimal solution from non-inferior solutions in turn is adopted instead of the ancient method.The experimental results show that the modified MaxMin-PSO algorithm converges more quickly and efficiently to Pareto solutions and achieve a well distribution.It also restrains the radiation of low dimension multi-objectives constrained functions. |
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| Keywords: | particle swarm algorithm MaxMin function turn list punish function |
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