Abstract Weight information of the attributes plays a pivotal role in multi-attribute decision making (MADM) problems. Oftentimes, a decision maker may try to manipulate this weight information to persuade a particular rank order of the alternatives of his/her interest. In the literature, this type of manipulation is known as strategic manipulation of the weight information. In this study, we consider the manipulation of weight information strategically in a TOPSIS MADM method under two scenarios: (1) completely unknown weight information i.e. the decision maker does not provide any weight information; (2) incomplete weight information i.e. the decision maker provides only partial preference information over the attributes. This weight manipulation problem is formulated as a mixed integer non-linear programming (MINLP) problem which is highly constrained. Therefore, for solving the MINLP model, a genetic algorithm based solution procedure is developed. A practical example is presented to illustrate the strategic manipulation procedure.

中文翻译：

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一种多属性决策的进化策略权重操纵方法：TOPSIS法

摘要 属性的权重信息在多属性决策（MADM）问题中起着举足轻重的作用。通常，决策者可能会尝试操纵此权重信息以说服他/她感兴趣的备选方案的特定等级顺序。在文献中，这种类型的操纵被称为权重信息的策略操纵。在本研究中，我们考虑在两种情况下在 TOPSIS MADM 方法中策略性地操纵权重信息：（1）完全未知的权重信息，即决策者不提供任何权重信息；(2) 不完整的权重信息，即决策者仅提供对属性的部分偏好信息。这个权重操作问题被表述为一个高度约束的混合整数非线性规划 (MINLP) 问题。因此，为了求解 MINLP 模型，开发了基于遗传算法的求解过程。给出了一个实际例子来说明战略操纵程序。