Strategic weight manipulation in multiple attribute decision making

Yucheng Dong, Yating Liu, Haiming Liang, Francisco Chiclana and Enrique Herrera-Viedma

Omega, 2018, vol. 75, issue C, 154-164

Abstract: In some real-world multiple attribute decision making (MADM) problems, a decision maker can strategically set attribute weights to obtain her/his desired ranking of alternatives, which we call the strategic weight manipulation of the MADM. In this paper, we define the concept of the ranking range of an alternative in the MADM, and propose a series of mixed 0–1 linear programming models (MLPMs) to show the process of designing a strategic attribute weight vector. Then, we reveal the conditions to manipulate a strategic attribute weight based on the ranking range and the proposed MLPMs. Finally, a numerical example with real background is used to demonstrate the validity of our models, and simulation experiments are presented to show the better performance of the ordered weighted averaging operator than the weighted averaging operator in defending against the strategic weight manipulation of the MADM problems.

Keywords: Multiple attribute decision making; Strategic weight manipulation; Average; Ranking (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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DOI: 10.1016/j.omega.2017.02.008

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