基于投影面的多目标优化问题目标分解进化算法

doi:10.3969/j.issn.2095-2198.2024.02.015

沈阳化工大学学报 ›› 2024, Vol. 38 ›› Issue (2): 185-192.doi: 10.3969/j.issn.2095-2198.2024.02.015

• 信息与计算机工程 • 上一篇

基于投影面的多目标优化问题目标分解进化算法

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

出版日期:2024-04-30 发布日期:2025-01-02
通讯作者: 陈未如
作者简介:刘宝（1994—），男，山西太原人，硕士研究生在读，主要从事多目标优化问题和进化算法的研究.

Evolutionary Algorithm for Solving Multi-Objective Optimization Problem Based on Projection Plane with Objective Decomposition

1.Shenyang University of Chemical Technology, Shenyang 110142, China; 2. Key Laborotary of Industrial Intelligence Technology on Chemical Process, Shenyang 110142, China

Online:2024-04-30 Published:2025-01-02

摘要/Abstract

摘要：

针对求解多目标优化问题存在解规模较大的问题，研究了如何得到决策条件下所需要的解，而不是多目标问题的全部解.现有多目标算法研究主要集中在解的分布性和收敛性上，很少考虑解数量方面的相关问题.根据决策需求并利用基于投影面的多目标优化算法对多目标优化问题的目标空间进行目标分解，设置不同目标函数构成投影面和自由维，建立满足用户决策条件的目标空间.在目标空间中对构成投影面的目标函数进行目标范围限定，利用空间距离获取投影面适应度，并在自由维上采用基于分解策略的多目标进化算法MOEA/D中的聚合函数作为适应度函数.通过相关的实验测试与分析，证明了基于投影面的多目标优化问题目标分解进化算法（MOEA/DP）能够有效解决确定目标域的多目标优化问题.

关键词: 多目标优化')">

多目标优化, 投影面, 进化算法, 目标范围限定

Abstract:

In order to solve the question that the multi-objective optimization problem with many solutions,this paper studies how to obtain the required solutions under decision condition,rather than all the solutions of the multi-objective problem.At present,the existing multi-objective algorithms mainly focus on the distribution and convergence of the solutions,and rarely consider the number of solutions.According to decision condition,using the multi-objective optimization algorithm based on plane to decompose the objective function of the multi-objective optimization problem,and different objective functions are divide into the plane and free dimension,so the objective space under the user′s decision conditions is established.In the objective space,limit the objective range of the objective function that constitutes the projection plane in the objective space,use the spatial distance to obtain the fitness of the projection plane,and use the aggregation function in the MOEA/D algorithm based on the decomposition strategy as the fitness function on the free dimension.Through related experimental tests and analysis,it is proved that Evolutionary Algorithm for solving Multi-objective Optimization Problem Based on Projection Plane with objective decomposition can effectively solve the multi-objective optimization problem of determining the objective domain.

Key words: multi-objective optimization')">

multi-objective optimization, projection plane, evolutionary algorithm, objective scope limit

刘宝1, 2, 杨爽1, 2, 马畅畅1, 2, 鹿晓梦1, 2, 陈未如1, 2.

基于投影面的多目标优化问题目标分解进化算法 [J]. 沈阳化工大学学报, 2024, 38(2): 185-192.

LIU Bao1, 2, YANG Shuang1, 2, MA Changchang1, 2, LU Xiaomeng1, 2, CHEN Weiru1, 2.

Evolutionary Algorithm for Solving Multi-Objective Optimization Problem Based on Projection Plane with Objective Decomposition [J]. Journal of Shenyang University of Chemical Technology, 2024, 38(2): 185-192.

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基于投影面的多目标优化问题目标分解进化算法

Evolutionary Algorithm for Solving Multi-Objective Optimization Problem Based on Projection Plane with Objective Decomposition

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