[1]马畅畅,汪 坤,鹿晓梦,等.一种确定目标域多目标优化算法 NSGA/ P[J].计算机技术与发展,2022,32(05):15-21.[doi:10. 3969 / j. issn. 1673-629X. 2022. 05. 003]
　MA Chang-chang,WANG Kun,LU Xiao-meng,et al.A Multi-objective Optimization Algorithm for Determinant Objective Domain NSGA / P[J].,2022,32(05):15-21.[doi:10. 3969 / j. issn. 1673-629X. 2022. 05. 003]
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一种确定目标域多目标优化算法 NSGA/ P()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年05期
页码:
15-21
栏目:
人工智能
出版日期:
2022-05-10

文章信息/Info

Title:
A Multi-objective Optimization Algorithm for Determinant Objective Domain NSGA / P
文章编号:
1673-629X(2022)05-0015-07
作者:
马畅畅1; 2 ; 汪 坤1; 2 ; 鹿晓梦1; 2 ; 陈未如1; 2
1. 沈阳化工大学 计算机科学与技术学院,辽宁 沈阳 110142;
2. 辽宁省化工过程工业智能化技术重点实验室,辽宁 沈阳 110142
Author(s):
MA Chang-chang1; 2 ; WANG Kun1; 2 ; LU Xiao-meng1; 2 ; CHEN Wei-ru1; 2
1. School of Computer Science and Technology,Shenyang University of Chemical Technology,Shenyang 110142,China;
2. Liaoning Key Laboratory of Industrial Intelligence Technology on Chemical Process,Shenyang 110142,China
关键词:
多目标优化; 确定目标域; 投影面; 自由维; NSGAII; MOEA / P
Keywords:
multi-objective optimization; determinant objective domain; projection plane; free dimension; NSGAII; MOEA / P
分类号:
TP301. 6
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 05. 003
摘要:
为了使多目标进化算法在求解多目标优化问题时能够更好地收敛到 Pareto 最优解,在 NSGA-II 算法基础上,借鉴MOEA / P 算法的思想,提出确定目标域多目标优化算法 NSGA / P,将 NSGA-II 算法与 MOEA / P 算法思想结合,实现确定目标域内的最优值的求取。 NSGA-II 是一种求解多目标优化问题的经典算法;MOEA / P 是一种基于投影面的多目标优化算法,更加适用于求解超多目标优化问题。 NSGA / P 算法采用 MOEA / P 思想,将整个决策空间划分为投影面和自由维,根据决策者的需求确定目标域,以此为投影面,并在自由维上采用 NSGA-II 算法进行寻优,提高了算法的效率。 通过对大量的实验结果分析及验证,发现 NSGA / P 算法增加了解的多样性,提高了算法的收敛性能,并有效地改善了求解复杂优化问题的能力,证明 NSGA / P 算法在求取确定目标域的多目标优化问题上有一定的优势。
Abstract:
In order to make the multi-objective evolutionary algorithm can better converge to the Pareto optimal solution when solving the multi-objective optimization problem,a multi-objective optimization algorithm NSGA / P is proposed based on NSGA-II algorithm and the idea of MOEA / P algorithm. The NSGA-II algorithm is combined with the idea of MOEA / P algorithm to achieve the optimal value in the determinant objective domain. NSGA-II is a classical algorithm for solving multi-objective optimization problems. MOEA / P is a multi- objective optimization algorithm based on projection plane, which is more suitable for solving many - objective optimization problems. NSGA / P algorithm adopts the idea of MOEA / P,the whole decision space is divided into projection plane and free dimension,and the objective domain is determinant according to　　the needs of the decision maker,which is used as the projection plane. In the free dimension,NSGA - II algorithm is used for optimization, which improves the efficiency of the algorithm. Through the analysis and verification of a large number of experimental results,it is found that the NSGA / P algorithm increases the diversity of the set,improves the convergence performance of the algorithm,and effectively improves the ability to solve complex optimization problems. It is proved the NSGA / P algorithm have a certain advantage in calculating determinant objective domain on the multi-objective optimization problem.

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更新日期/Last Update: 2022-05-10