Imprecise Shannon's Entropy and Multi Attribute Decision Making

By F. Lotfi, Reza Fallahnejad. Entropy, 2010

394 citations recorded by the source corpus.

Abstract: Finding the appropriate weight for each criterion is one of the main points in Multi Attribute Decision Making (MADM) problems. Shannon’s entropy method is one of the various methods for finding weights discussed in the literature. However, in many real life problems, the data for the decision making processes cannot be measured precisely and there may be some other types of data, for instance, interval data and fuzzy data. The goal of this paper is the extension of the Shannon entropy method for the imprecise data, especially interval and fuzzy data cases. Keywords : multi attribute decision making; entropy; imprecise data MSC Codes: 90B50, 90C29, 90C70 1. Introduction Multiple attribute decision making (MADM) refers to making preference decisions (e.g., evaluation, prioritization, and selection) over the available alternatives that are characterized by multiple, usually conflicting, attributes. The structure of the alternative performance matrix is depicted in Table 1, where

Subfields: Control and Systems Engineering, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4bbfef0667f1b31296c91ed3b1f8d195428a8e62

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Citations in the corpus

The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming (2014, methodology): “This method needs a decision matrix that its elements should be normalized as follows [30].”
Quantifying the chemical beauty of drugs. (2012, methodology): “Rather than assigning weights subjectively, we rationalized that the optimal set of weights is that which maximizes information content, which can be measured by calculating the Shannon entropy (SE”
Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD (2021, methodology): “These are such methods as entropy weighting method (EWM) (Lotfi & Fallahnejad, 2010; Wu et al., 2011; He et al., 2016), CRiteria Importance Through Inter-criteria Correlation (CRITIC) (Diakoulaki et al., 1995), standard deviation (SD) and their modifications (Jahan et al., 2012; Žižović et al.,…”
Selection and performance assessment of Phase Change Materials for heating, ventilation and air-conditioning applications (2015, methodology): “The relative entropy measurement of attribute data has a direct bearing on the outcome of any decision making process [43–45].”