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Comparison of weights in TOPSIS models. (English) Zbl 1066.90054
Summary: TOPSIS is a multiple criteria method to identify solutions from a finite set of alternatives based upon simultaneous minimization of distance from an ideal point and maximization of distance from a nadir point. TOPSIS can incorporate relative weights of criterion importance. This paper reviews several applications of TOPSIS using different weighting schemes and different distance metrics, and compares results of different sets of weights applied to a previously used set of multiple criteria data. Comparison is also made against SMART and centroid weighting schemes. TOPSIS was not found to be more accurate, but was quite close in accuracy. Using first-order and second-order metrics were found to be quite good, but the infinite order (Chebyshev norm, $$L_\infty$$) was found to decline in accuracy.

##### MSC:
 90B50 Management decision making, including multiple objectives
##### Keywords:
Multiple criteria; Selection methods