Abstract
Article history: Received January 15, 2013 Accepted October 12, 2013 Available online November 4 2013 Decision making problem is the process of finding the best option out of all feasible alternatives. There are some methods for solving Multiple Criteria Decision-Making problems and Simple Additive Weighting (SAW) is one of the most popular ones. In this paper, among multi-criteria models in making complex decisions and multiple attribute models for the most preferable choice, SAW technique is extended using interval numbers. For this purpose, we first propose a method for extending Entropy method for dealing with interval data, and then the extended SAW method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method. The extended SAW method is an algorithm to determine the most preferable choice out of all possible choices, when the input data are stated in interval. © 2014 Growing Science Ltd. All rights reserved.
Highlights
Decision-making problem is considered as a process of detecting the best alternative from all of the feasible alternatives
We first propose a method for extending Entropy method for dealing with interval data, and the extended Simple Additive Weighting (SAW) method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method
Multi-Attribute Decision Making (MADM) along with multi-objective decision making (MODM) are the most well-known categories of decision making, which is a branch of a general class of multi-criteria decision making (MCDM) in operations research models and they deal with decision problems under the presence of a number of decision criteria (Zeleny, 1982; Zimmermann, 1991)
Summary
Decision-making problem is considered as a process of detecting the best alternative from all of the feasible alternatives. An evaluation score is calculated for each alternative by multiplying the scaled value given to the alternative of that attribute with the weights of relative importance directly assigned by decision maker followed by summing of the products for all criteria. The advantage of this method is that it is a proportional linear transformation of the raw data, which means that the relative order of magnitude of the standardized scores remains equal (Afshari, et al, 2010).In this new method, we try to use entropy method with interval data for development of SAW method with interval data.
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