Comparison of weights in TOPSIS models

TOPSIS is a multiple criteria method to identify solutions from a finite set of alternativesbased 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 severa...

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Bibliographic Details
Published in:Mathematical and computer modelling 2004-10, Vol.40 (7), p.721-727
Main Author: Olson, D.L.
Format: Article
Language:English
Subjects:
Approximations and expansions
Exact sciences and technology
Mathematical analysis
Mathematics
Methods of scientific computing (including symbolic computation, algebraic computation)
Multiple criteria
Numerical analysis. Scientific computation
Sciences and techniques of general use
Selection methods
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Summary:TOPSIS is a multiple criteria method to identify solutions from a finite set of alternativesbased 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 (Tchebycheff norm, L-∞) was found to decline in accuracy.
ISSN:0895-7177
1872-9479
DOI:10.1016/j.mcm.2004.10.003