| 一种新颖的多目标优化算法 |
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| 引用本文： | 徐远清,陈祥光,王丽.一种新颖的多目标优化算法[J].广西师范大学学报(自然科学版),2006,24(4):131-134. |
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| 作者姓名： | 徐远清 陈祥光 王丽 |
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| 作者单位： | 北京理工大学,化工与环境学院,北京,100081 |
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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： | 粒子群算法的特性使得其在解决多目标优化问题时具有很强的竞争性,提出了一种结合小生境思想和在线归档策略的多目标粒子群优化算法,该算法能够在进化过程中保持优良种群。通过3个测试函数来评价算法性能并将算法与NSGA-II做比较,结果表明提出的算法的时间耗费明显小于NSGA-II算法且解集沿着Pareto非劣最优目标域有很好的扩展性。
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| 关 键 词： | 多目标 粒子群优化 适应值共享 归档 |
| 文章编号： | 1001-6600（2006）04-0131-04 |
| 收稿时间： | 2006-05-31 |
| 修稿时间： | 2006年5月31日 |
Original Multi-Objective Optimization Algorithm |
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| XU Yuan-qing,CHEN Xiang-guang,WANG Li.Original Multi-Objective Optimization Algorithm[J].Journal of Guangxi Normal University(Natural Science Edition),2006,24(4):131-134. |
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| Authors: | XU Yuan-qing CHEN Xiang-guang WANG Li |
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| Institution: | School of Chemical Engineering and Environment,Beijing Institute of Technology,Beijing 100081,China |
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| Abstract: | Particle swarm optimization has been a competitive heuristic to solve multi-objective optimization problems.In this paper,a new approach combined online elite archiving and fitness sharing is proposed for multi-objective optimization problems.Three test functions have been used to evaluate the performance of proposed approach.What's more,the comparison of average time between the proposed method and NSGA-II has been done.The results indicate that the proposed approach generates a satisfactory approximation of the Pareto front with evenly distributed solution along it. |
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| Keywords: | multi-objective particle swarm optimization fitness sharing archiving |
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