理论(学习稳定性)
多准则决策分析
数学
构造(python库)
班级(哲学)
数学优化
计算机科学
人工智能
机器学习
程序设计语言
标识
DOI:10.1016/0377-2217(88)90254-8
摘要
In this paper we study the stability of the results given by a wide class of MCDA methods to changes of the weights of the criteria. Three aspects of stability are discussed. In each case we propose to construct stability intervals for the weights of either single criteria or groups of criteria. A necessary and sufficient condition for stability is also considered. The use of these instruments is demonstrated with a numerical example.
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