Decision making under conflicting environment: a new MCDM method

Das, Manik Chandra; Sarkar, Bijan; Ray, Siddhartha

doi:10.1504/ijads.2012.046505

Cited by 36 publications

(23 citation statements)

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“…This method fixes the attribute weights by constituting experts' judgment matrix, and this method does not need to test the consistency of judgment matrix. In this point, it is an advantage over AHP method, and thus also leads the group eigenvalue method more simple and convenient [11][12][13][14][15][16].The detailed conception and steps of group eigenvalue method are given as follows [10]:…”

Section: Group Eigenvalue Methodsmentioning

confidence: 99%

A Novel Machine Selection Method Combining Group Eigenvalue Method with TOPSIS Method

Yang¹,

Xiong³

2016

IJFGCN

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Section: Group Eigenvalue Methodsmentioning

confidence: 99%

A Novel Machine Selection Method Combining Group Eigenvalue Method with TOPSIS Method

Yang¹,

Xiong³

2016

IJFGCN

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“…The MOORA method is applied for the assessment of an indoor environment of dwelling houses. In this paper, the experiment was chosen for research according to the related works and results presented in Das, Sarkar, and Ray (2012). The MOORA (Brauers & Zavadskas, 2006, 2009 procedure is one of the simplest multicriteria methods in selecting the corresponding decision attributes.…”

Section: Related Literaturementioning

confidence: 99%

Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA

Sarkar

Panja

Das

et al. 2015

Production & Manufacturing Research

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The purpose of this paper is to find out an efficient decision support method for non-traditional machine selection. It seeks to analyze potential non-traditional machine selection attributes with a relatively new MCDM approach of MOORA and MOOSRA method. The use of MOORA and MOOSRA method has been adopted to tackle subjective evaluation of information collected from an expert group. An example case study is shown here for better understanding of the said selection module which can be effectively applied to any other decision-making scenario. The method is not only computationally very simple, easily comprehensible, and robust, but also believed to have numerous subjective attributes. The rankings are expected to provide good guidance to the managers of an organization to select a feasible non-traditional machine. It shall also provide a good insight for the non-traditional machine manufacturer who might encourage research work concerning non-traditional machine selection.

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“…First MOOSRA method has been developed by Das et al [21]. Generally, the MOOSRA methodology starts with the formulation of decision matrix which has in general four parameters, namely: alternatives, criteria or attributes, individual weights or significance coefficients of each criteria and measure of performance of alternatives with respect to the criteria.…”

Section: Moosramentioning

confidence: 99%

“…The detailed descriptions of MOORA method has been explored in literature [20]. However the basic assumptions of the MOORA method [21] hold good for MOOSRA method also. The definite rewards of MOORA method is (like-less computational time, very simple and stable, minimum mathematical calculations involved, etc.)…”

Section: Introductionmentioning

confidence: 99%

Green Cutting Fluid Selection Using Moosra Method

Jagadish¹

2014

IJRET

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In every manufacturing process, cutting fluid is the key source of environmental pollution, with most favourable selection of cutting fluid for the green manufacturing(GM) being an essential for reducing the environmental pollution. The objective factors considered for the traditional selection are of two: cost(C) and quality (Q) but green factors also to be considered from the GM point of view. The aim of this research is to select the finest cutting fluid that minimize the environmental impact (E), cost(C) and maximize the quality (Q). This paper presents a new method, namely, multi-objective optimisation on the basis of simple ratio analysis (MOOSRA). A case study of cutting fluid selection for gear hobbing process was presented to validate the proposed model. The obtained result using MOOSRA has been compared with Analytical Hierarchical Process (AHP) and Decision Making Framework (DMF). The result shows that Syntilo 9930c is optimal in comparison with other.

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Decision making under conflicting environment: a new MCDM method

Cited by 36 publications

References 0 publications

A Novel Machine Selection Method Combining Group Eigenvalue Method with TOPSIS Method

A Novel Machine Selection Method Combining Group Eigenvalue Method with TOPSIS Method

Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA

Green Cutting Fluid Selection Using Moosra Method

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