"An evolutionary strategic weight manipulation approach for multi-attribute decision making: TOPSIS method"
Type of publication: International Journal
Year of publication: 2021
Authors: Bapi Dutta
Director: Son Duy Dao, Luis Martínez, Mark Goh
Type: "International Journal of Approximate Reasoning"
Volumen: 129
Pagination: 64-83
ISSN number: "0888-613X"
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."
URL: "http://www.sciencedirect.com/science/article/pii/S0888613X20302620"
DOI: https://doi.org/10.1016/j.ijar.2020.11.004