修正免疫克隆约束多目标优化算法  

Modified Immune Clonal Constrained Multi-Objective Optimization Algorithm

作　　者：尚荣华[1] 焦李成[1] 胡朝旭[1] 马晶晶[1] 

机构地区：[1]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

出　　处：《软件学报》2012年第7期1773-1786,共14页Journal of Software

基　　金：国家自然科学基金(61001202;61003199);中国博士后科学基金(201104658;20090451369;200801426;20080431228);陕西省自然科学基础研究计划(2009JQ8015;2010JQ8023);国家教育部博士点基金(20100203120008;20090203120016;200807010003);高等学校学科创新引智计划(B07048);教育部'长江学者和创新团队发展计划'(IRT1170)

摘　　要：针对约束多目标优化问题,提出修正免疫克隆约束多目标优化算法.该算法通过引进一个约束处理策略,用一个修正算法对个体的目标函数值进行修正,并对修正后的目标函数值采用免疫克隆算法进行优化,用一个精英种群对可行非支配解进行存储.该算法在优化过程中,既保留了非支配可行解,也充分利用了约束偏离值小的非可行解,同时引进整体克隆策略来提高解分布的多样性.通过对约束多目标问题的各项性能指标的测试以及和对比算法的比较可以看出:该算法在处理约束多目标优化测试问题时,所得解的多样性得到了一定的提高.同时,解的收敛性和均匀性也得到了一定的改进.This paper proposes a modified immune clonal constrained multi-objective algorithm for constrained multi-objective optimization problems. By introducing a new constrained handling strategy to modify the objective values of individuals, the proposed algorithm optimizes the individuals with the modified objective values and stores the non-dominated feasible individuals in an elitist population. In the optimization process, the algorithm not only preserves the non-dominated feasible individuals, but also utilizes the infeasible solutions with smaller constrained violation values. Meanwhile the new algorithm introduces the overall cloning strategy to improve the distribution diversity of the solutions. The proposed algorithm has been tested on several popular constrained test problems and compared with the other two constrained multi-objective optimization algorithms. The results show that the optimal solutions of the proposed algorithm are more diverse than the other two algorithms and better in terms of convergence and uniformity.

关 键 词：约束多目标优化 免疫克隆 约束处理策略 约束偏离值 非支配解 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]