Multi-objective Evolutionary Algorithm with Weight Preference

Jiang Shan; Chen Lei; Liu Hai-lin

doi:10.3969/j.issn.1007-7162.2016.01.013

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Multi-objective Evolutionary Algorithm with Weight Preference

更新时间：2026-05-27

- Multi-objective Evolutionary Algorithm with Weight Preference
- Vol. 33, Issue 1, Pages: 67-72(2016)
- 作者机构：
- 作者简介：
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- DOI：10.3969/j.issn.1007-7162.2016.01.013
  CLC：
- Online First：16 January 2016，
  
  Published：2016
- 稿件说明：
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江珊, 陈磊, 刘海林. 带有权重偏好的多目标进化算法[J]. 广东工业大学学报, 2016, 33(1): 67-72.

Jiang Shan, Chen Lei, Liu Hai-lin. Multi-objective Evolutionary Algorithm with Weight Preference[J]. 2016, 33(1): 67-72.
江珊, 陈磊, 刘海林. 带有权重偏好的多目标进化算法[J]. 广东工业大学学报, 2016, 33(1): 67-72. DOI： 10.3969/j.issn.1007-7162.2016.01.013.

Jiang Shan, Chen Lei, Liu Hai-lin. Multi-objective Evolutionary Algorithm with Weight Preference[J]. 2016, 33(1): 67-72. DOI： 10.3969/j.issn.1007-7162.2016.01.013.

摘要

对于现实生活中的一些多目标优化问题，往往存在着多个决策者的偏好.提出了一种新的偏好方式：决策者对目标函数的权重偏好，该方法在Delphi法下由决策者对目标函数的重要性打分形成，能够更好地体现出决策者的偏好，并且简单易行.结合M2M算法，形成了一种求解多目标优化问题的混合算法.数值实验显示

在不同偏好下，多目标优化问题的结果也不一样，这与实际情形相吻合.在实际生活中，这种方法也具有一定的现实意义.

Abstract

For the multi-objective optimization in real life，there are many preferences of decision makers. This paper proposes a new preference: the weight preference of objective function which derives and scores from its importance according to policy makers by Delphi method. This preference

expressive and facilitating

combines with M2M algorithm into a hybrid algorithm for solving multi-objective optimization problems. The experiments show that various preferences lead to different results in working out the multi-objective optimization problem

which coincides with the actual practice. Apart from its theoretical contribution

this preference also has its realistic significance.

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