| 基于自适应网格的多目标粒子群优化算法 |
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| 引用本文： | 杨俊杰,周建中,方仍存,李英海,刘力.基于自适应网格的多目标粒子群优化算法[J].系统仿真学报,2008,20(21):5843-5847. |
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| 作者姓名： | 杨俊杰 周建中 方仍存 李英海 刘力 |
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| 作者单位： | 华中科技大学水电与数字化工程学院 |
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| 基金项目： | 水利部公益性行业科研专项经费项目，中国博士后科学基金 |
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| 摘 要： | 针对现有多目标进化算法计算复杂度高,搜索效率低等缺点,提出了基于自适应网格的多目标粒子群优化(AGA-MOPSO)算法,其特点包括:评估非劣解集中粒子密度估计信息的自适应网格算法;能够平衡全局和局部搜索能力的基于AGA的Pareto最优解搜索技术;删除非劣解集集中品质差的多余粒子以维持非劣解集在一定规模的基于AGA的非劣解集截断技术.仿真计算表明,和文献中典型的多目标进化算法比较,AGA-MOPSO算法在求解复杂大规模优化问题方面表现了良好的性能.
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| 关 键 词： | 多目标 优化 粒子群优化 自适应网格算法 |
Multi-objective Particle Swarm Optimization Based on Adaptive Grid Algorithms |
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| YANG Jun-jie,ZHOU Jian-zhong,FANG Reng-cun,LI Ying-hai,LIU Li.Multi-objective Particle Swarm Optimization Based on Adaptive Grid Algorithms[J].Journal of System Simulation,2008,20(21):5843-5847. |
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| Authors: | YANG Jun-jie ZHOU Jian-zhong FANG Reng-cun LI Ying-hai LIU Li |
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| Abstract: | On the basis of analyzing such shortcomings of the exiting multi-objective evolutionary algorithms as high complexity of calculation and low searching efficiency,the multi-objective particle swarm optimization based on adaptive grid algorithm(AGA-MOPSO) was proposed,and it employs three techniques:adaptive grid algorithms(AGA),which can obtain the valid density value of particles in Archive set;Pareto optimal solution searching algorithm based on AGA,which can guide the particles searching efficiently in problem space;Archive pruning techniques based on AGA,which can remove inferior particles in Archive set.Compared with the representative MOEAs,AGA-MOPSO shows its effectiveness and efficiency in solving complex large scale optimization problems. |
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| Keywords: | multiple objectives optimization particle swarm optimization(PSO) adaptive grid algorithms(AGA) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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