Abstract
Article history: Received February 25, 2016 Received in revised format: March 28, 2016 Accepted August 12, 2016 Available online August 12 2016 Multiple attribute decision making (MADM) methods are very useful in choosing the best alternative among the available finite but conflicting alternatives. TOPSIS is one of the MADM methods, which is simple in its methodology and logic. In TOPSIS, Euclidean distances of each alternative from the positive and negative ideal solutions are utilized to find the best alternative. In literature, apart from Euclidean distances, the city block distances have also been tried to find the separations measures. In general, the attribute data are distributed with unequal ranges and also possess moderate to high correlations. Hence, in the present paper, use of statistical distances is proposed in place of Euclidean distances. Procedures to find the best alternatives are developed using statistical and weighted statistical distances respectively. The proposed methods are illustrated with some industrial problems taken from literature. Results show that the proposed methods can be used as new alternatives in MADM for choosing the best solutions. Growing Science Ltd. All rights reserved. 7 © 201
Highlights
Multiple attribute decision making (MADM) methods involve the selection of best alternative from the available limited but conflicting alternatives
It is evident from the results that the last choice cannot be alternative 5, as the Manufacturing Cost (MC) value is minimum for this alternative and the weight given to MC is very high, and some popular methods suggested this as the first alternative
A new approach to multiple attribute decision making has been suggested by introducing the statistical distance in place of Euclidian distance for TOPSIS
Summary
Multiple attribute decision making (MADM) methods involve the selection of best alternative from the available limited but conflicting alternatives. This is often achieved by finding the order of preference for all the alternatives and choosing the rank one alternative as the best for practical purposes. Hwang and Yoon (1981) cite the first MADM application by Churchman et al (1957) which uses the simple additive weighting method to solve a decision making problem. Use of statistical distances from the positive and the negative ideal solutions is proposed in TOPSIS methodology. Final conclusions on the proposed methodology are drawn in last Section
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