| 基于NSGA-II的改进多目标遗传算法 |
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| 引用本文： | 陈小庆 侯中喜 郭良民 罗文彩. 基于NSGA-II的改进多目标遗传算法[J]. 计算机应用, 2006, 26(10): 2453-2456 |
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| 作者姓名： | 陈小庆 侯中喜 郭良民 罗文彩 |
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| 作者单位： | 国防科学技术大学航天与材料工程学院,湖南长沙410073 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 在已有多目标优化算法（NSGA-II）研究和分析的基础上，为加快收敛速度，提高收敛精度，设计了新的初始筛选机制，改进了交叉算子的系数生成，提出了更为合理的排挤机制。通过典型应用函数的计算测试，结果表明：上述改进不仅具有较高的计算效率，而且能够得到分布更为合理的解，且能保持解的多样性分布。
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| 关 键 词： | 多目标优化 遗传算法 排挤机制 交叉算子 初始种群 |
| 文章编号： | 1001-9081（2006）10-2453-04 |
| 收稿时间： | 2006-04-20 |
| 修稿时间： | 2006-04-202006-07-26 |
Improved multi-objective genetic algorithm based on NSGA-II |
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| CHEN Xiao-qing,HOU Zhong-xi,GUO Liang-min,LUO Wen-cai. Improved multi-objective genetic algorithm based on NSGA-II[J]. Journal of Computer Applications, 2006, 26(10): 2453-2456 |
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| Authors: | CHEN Xiao-qing HOU Zhong-xi GUO Liang-min LUO Wen-cai |
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| Affiliation: | College of Aerospace and Material Engineering, National University of Defense Technology, Changsha Hunan 410073, China |
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| Abstract: | Based on the study and analysis of NSGA-II algorithm, a new initial screening mechanism was designed, coefficient generating of crossover arithmetic operator was improved and more reasonable crowding mechanism was proposed. In this way, convergence was speeded up and its precision was improved. The testing results by representative applied functions show that with the improvements higher computational efficiency and more reasonable distributed solution can be obtained, and diversified distribution of the solutions can be maintained. |
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| Keywords: | multi-objective optimization genetic algorithm crowing mechanism crossover arithmetic operator initial population |
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