4.7 Article

Fair framework for multiple criteria decision making

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 124, Issue -, Pages 379-392

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2018.07.039

Keywords

Multiple criteria decision making; Fair framework; Criterion weights; Evidential reasoning approach; Evidential reasoning algorithm

Funding

  1. National Natural Science Foundation of China [71622003, 71571060, 71690235, 71690230, 71521001, 71501056, 71531008]

Ask authors/readers for more resources

As the determination of criteria weights is important for multiple criteria decision making, a number of attempts have been made to assign weights to criteria. However, whether criterion weight assignment is fair to each criterion and to each alternative is rarely taken into account. To address this issue, in this paper, we propose a fair framework in the context of the evidential reasoning approach, which is a type of multiple criteria utility function method. In the fair framework, two strategies are prepared for a decision maker to choose, which are the superior strategy and the inferior strategy. To achieve the objective in line with the selected strategy, two levels of fairness including the fairness among criteria and the fairness among alternatives are defined based on the performances of alternatives on each criterion. By following the two levels of fairness defined, two optimization models are constructed successively to generate possible sets of fair criterion weights. With a view to making all possible sets of fair criterion weights treated in generating a solution, they are incorporated into another optimization model constructed to generate the minimum and maximum expected utilities of each alternative, by which the solution is made with a decision rule preferred by the decision maker. A supplier evaluation problem is analyzed to demonstrate the applicability and validity of the fair framework.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available