A Meta-Goal Programming approach to cardinal preferences aggregation in multicriteria problems
A Meta-Goal Programming approach to cardinal preferences aggregation in multicriteria problems
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DOI：
10.1016/j.omega.2019.03.003
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发表时间：
2020-07-01
影响因子：
6.9
通讯作者：
Ruiz, Francisco
中科院分区：
文献类型：
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作者：
Benitez-Fernandez, Amalia;Ruiz, Francisco
解决多准则决策问题通常需要评估某些偏好信息。在某些情况下，这些信息必须由几个人或社会团体提供，这些个人评估需要汇总为单一的全球偏好。这个基数偏好聚合问题已经解决了使用不同的技术，包括多准则决策。在本文中，元目标规划的方法，提出了不同的目标值可以设置在几个成就功能，衡量全球评估的良好性。这种方法由于其建模灵活性和找到平衡解决方案的能力而具有很强的优势。所提出的方法证明了一个说明性的例子和一系列的计算实验，它表明，元目标规划方法产生的结果与更好的值的成就函数比其他经典和多准则的方法。(C)2019爱思唯尔有限公司版权所有。
Solving multicriteria decision making problems often requires the assessment of certain preferential information. In some occasions, this information must be given by several individuals or social groups, and these individual assessments need to be aggregated into single global preferences. This cardinal preferences aggregation problem has been tackled using different techniques, including multicriteria decision making ones. In this paper, a Meta-Goal Programming approach is proposed, where different target values can be set on several achievement functions that measure the goodness of the global assessments. This methodology presents strong advantages due to its modeling flexibility and its ability to find balanced solutions. The proposed approach is demonstrated with an illustrative example and a series of computational experiments, and it is shown that the Meta-Goal Programming method produces results with better values of the achievement functions than other classical and multicriteria approaches. (C) 2019 Elsevier Ltd. All rights reserved.