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求解偏好多目标优化的克隆选择算法
引用本文:杨咚咚,焦李成,公茂果,余航.求解偏好多目标优化的克隆选择算法[J].软件学报,2010,21(1):14-33.
作者姓名:杨咚咚  焦李成  公茂果  余航
作者单位:西安电子科技大学,智能信息处理研究所,陕西,西安,710071;智能感知与图像理解教育部重点实验室(西安电子科技大学),陕西,西安,710071
基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60703107, 60703108 (国家自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2009AA12Z210 (国家高技术研究发展计划(863)); the National Basic Research Program of China under Grant No.2006CB705707 (国家重点基础研究发展计划(973)); the Program for Cheung Kong Scholars and Innovative Research Team in University of China under Grant No.IRT0645 (长江学者和创新团队支持计划)
摘    要:目标维数较高的多目标优化问题的难题在于非支配解急剧增加,经典算法由于缺乏足够的选择压力导致性能急剧下降.提出了基于偏好等级的免疫记忆克隆选择优化算法,用于解决目标维数较高的多目标优化问题.利用决策者提供的偏好信息来为抗体分配偏好等级,根据该值比例克隆抗体,增大抗体的选择压力,加快收敛速率.根据偏好信息来缩减Pareto前沿,并用有限的偏好解估计该前沿.同时,建立了免疫记忆种群来保留较好的非支配抗体,采用ε支配机制来保持记忆抗体种群的多样性.实验结果表明,对于2目标的偏好多目标问题以及高达8目标的DTLZ2和DTLZ3问题,该算法取得了一定的实验效果.

关 键 词:人工免疫系统  偏好多目标优化  偏好等级  ε支配
收稿时间:2008/8/25 0:00:00
修稿时间:2008/12/29 0:00:00

Clone Selection Algorithm to Solve Preference Multi-Objective Optimization
YANG Dong-Dong,JIAO Li-Cheng,GONG Mao-Guo and YU Hang.Clone Selection Algorithm to Solve Preference Multi-Objective Optimization[J].Journal of Software,2010,21(1):14-33.
Authors:YANG Dong-Dong  JIAO Li-Cheng  GONG Mao-Guo and YU Hang
Affiliation:YANG Dong-Dong1,2+,JIAO Li-Cheng1,2,GONG Mao-Guo1,YU Hang1,2 1(Institute of Intelligent Information Processing,Xidian University,Xi\'an 710071,China) 2(Key Laboratory of Intelligent Perception , Image Underst,ing of Ministry of Education of China (Xidian University),China)
Abstract:The difficulty of current multi-objective optimization community lies in the large number of objectives. Lacking enough selection pressure toward the Pareto front,classical algorithms are greatly restrained. In this paper,preference rank immune memory clone selection algorithm (PISA) is proposed to solve the problem of multi-objective optimization with a large number of objectives. The nondominated antibodies are proportionally cloned by their preference ranks,which are defined by their preference informati...
Keywords:artificial immune system  preference multi-objective optimization  preference rank
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