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A Comparative Study on Decision Making Methods with Interval Data
Author(s) -
Aditya Chauhan,
Rahul Vaish
Publication year - 2014
Publication title -
journal of computational engineering
Language(s) - English
Resource type - Journals
eISSN - 2356-7260
pISSN - 2314-6443
DOI - 10.1155/2014/793074
Subject(s) - topsis , ideal solution , interval (graph theory) , computer science , data mining , multiple criteria decision analysis , entropy (arrow of time) , mathematical optimization , mathematics , operations research , physics , combinatorics , quantum mechanics , thermodynamics
Multiple Criteria Decision Making (MCDM) models are used to solve a number of decision making problems universally. Most of these methods require the use of integers as input data. However, there are problems which have indeterminate values or data intervals which need to be analysed. In order to solve problems with interval data, many methods have been reported. Through this study an attempt has been made to compare and analyse the popular decision making tools for interval data problems. Namely, I-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), DI-TOPSIS, cross entropy, and interval VIKOR (VlseKriterijumska Optimiza-cija I Kompromisno Resenje) have been compared and a novel algorithm has been proposed. The new algorithm makes use of basic TOPSIS technique to overcome the limitations of known methods. To compare the effectiveness of the various methods, an example problem has been used where selection of best material family for the capacitor application has to be made. It was observed that the proposed algorithm is able to overcome the known limitations of the previous techniques. Thus, it can be easily and efficiently applied to various decision making problems with interval data

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