区间多目标优化非支配排序云模型算法  

Non-dominated sorting cloud model algorithm for interval multi-objective optimization

作　　者：陈志旺[1] 黄兴旺[2] 陈志兴[3] 赵子铮 黄丽芳 

机构地区：[1]燕山大学河北省工业计算机控制工程重点实验室,河北秦皇岛066000 [2]燕山大学国家冷轧板带装备及工业工程技术研究中心,河北秦皇岛066000 [3]佳木斯电业局,黑龙江佳木斯154002 [4]西部超导材料科技股份有限公司,西安710018

出　　处：《计算机工程与应用》2017年第22期143-149,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61573305;No.61403331);河北省自然科学基金青年基金(No.F2014203099);燕山大学青年教师自主研究计划课题(No.13LGA006)

摘　　要：针对区间多目标优化问题,利用云模型对NSGA-Ⅱ算法进行改进,提出一种非支配排序云模型算法(NSCMA)。首先,从初始云团中随机选取一个云滴作为父代,通过正态云算子生成子代云滴,用来替代传统NSGA-Ⅱ遗传操作中的交叉和变异;其次,用约束条件对生成的云滴进行筛选处理,避免不可行解进入下一步算法;最后,运用区间占优关系对满足约束条件的解进行占优排序,对无法比较的同序值解计算拥挤距离。仿真结果验证了所设计算法的有效性。A kind of Non-dominated Sorting Cloud Model Algorithm（NSCMA）for solving interval multi-objective optimization is proposed, in which cloud model is used to improve the NSGA-Ⅱ algorithm. Firstly, genetic operator such as crossover and mutation in conventional NSGA-Ⅱ is replaced by normal cloud operator, and offspring cloud droplets are derived from random parent in initial cloud cluster. Secondly, generated cloud droplets are disposed and kept based on constraint conditions, so infeasible solution doesn＇t be left in the next algorithm. Finally, the feasible solution is sorted by interval dominant relationship, and then the crowding distance of incomparable same order solution is calculated. The simulations results have verified the effectiveness of the designed algorithm.

关 键 词：多目标优化 区间规划 约束优化问题 云模型 NSGA-Ⅱ 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]