An integrated approach to grey relational analysis, analytic hierarchy process and data envelopment analysis. Issue 1 (2nd September 2016)

• Record Type: Journal Article
• Authors: Pakkar, Mohammad Sadegh
• Is Part Of: Journal of centrum cathedra. Volume 9:Issue 1(2016)
• Page Start: 71
• Page End: 86
• Publication Date: 2016-09-02
• Subjects: Data envelopment analysis -- Grey relational analysis -- Analytic hierarchy process -- Multiple attribute decision making -- Fuzzy numbers -- Weighting; C02 -- C61 -- D81 -- M11; Industrial management -- Periodicals; Industrial management; Electronic journals; Periodicals; 330
• DOI: 10.1108/JCC-08-2016-0005
• Languages: English
• ISSNs: 1851-6599

Abstract

Abstract : Purpose: This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers. Design/methodology/approach: This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative. Findings: The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach. Originality/value: This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.