| 基于Pareto邻域交叉算子的多目标粒子群优化算法 |
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| 引用本文： | 屈敏,高岳林,江巧永.基于Pareto邻域交叉算子的多目标粒子群优化算法[J].计算机应用,2011,31(7):1789-1792. |
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| 作者姓名： | 屈敏 高岳林 江巧永 |
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| 作者单位： | 北方民族大学 信息与系统科学研究所,银川 750021 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 针对粒子群优化（PSO）算法局部搜索能力不足的问题，提出一种基于Pareto邻域交叉算子的多目标粒子群优化算法(MPSOP)。该算法利用粒子群优化算法和Pareto邻域交叉算子相结合的策略产生新种群，并利用尺度因子在线调节粒子群优化算法和Pareto邻域交叉算子的贡献量。数值实验选取6个常用测试函数并对NSGA-Ⅱ、SPEA2、MOPSO三个多目标算法进行比较，数值实验结果表明MPSOP算法的有效性。
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| 关 键 词： | 多目标优化 粒子群算法 Pareto邻域交叉算子 尺度因子 |
| 收稿时间： | 2010-12-31 |
| 修稿时间： | 2011-01-31 |
Multi-objective particle swarm optimization algorithm based on Pareto neighborhood crossover operation |
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| QU Min,GAO Yue-lin,JIANG Qiao-yong.Multi-objective particle swarm optimization algorithm based on Pareto neighborhood crossover operation[J].journal of Computer Applications,2011,31(7):1789-1792. |
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| Authors: | QU Min GAO Yue-lin JIANG Qiao-yong |
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| Affiliation: | Institute of Information and System Science, Beifang University of Nationalities, Yinchuan Ningxia 750021,China |
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| Abstract: | A multi-objective particle swarm optimization algorithm with Pareto neighborhood crossover operation (MPSOP) is proposed to solve the defect of local search for prrticle swarm optimization problems. MPSOP employs particle swarm optimization algorithm and Pareto neighborhood crossover operation to generate new population. A scaling factor used to balance contributions of particle swarm optimization algorithm and Pareto neighborhood crossover operation. Numerical experiments are compared with NSGA-II, SPEA2 and MOPSO on six benchmark problems. The numerical results show the effectiveness of the proposed MPSOP algorithm. |
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| Keywords: | multi-objective optimization particle swarm algorithm Pareto neighborhood crossover operation scaling factor |
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