Title: Robust strategies for mitigating operational and disruption risks: a fuzzy AHP approach

Authors: A.R. Singh; P.K. Mishra; Rajeev Jain; M.K. Khurana

Addresses: Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, 211004, India. ' Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, 211004, India. ' Department of Mechanical Engineering, Kalaniketan Polytechnic College Jabalpur, Jabalpur, 482001, India. ' Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, 211004, India

Abstract: Some supply chains continue to function smoothly and take short time to recover after a major disruption because they possessed 'robust' strategies for mitigating operational and disruption risks. In this paper, some of the strategies are proposed that make the supply chain more efficient and resilient. Linguistic and subjective evaluations take place in questionnaire form to find out the best strategy for mitigating risks in Indian manufacturing industries. Each linguistic variable has its own numerical value in predefined scale. In classical analytical hierarchy process (AHP), these numerical values are exact numbers whereas in fuzzy AHP method they are intervals between two numbers with most likely value. Therefore, fuzzy AHP approach is used because linguistic value can change person to person. In these circumstances, taking the fuzziness in to account will provide results that are not prone to risks. Our finding highlights the ranking of the different strategies to mitigate supply chain risks on the basis of weight and survey data.

Keywords: SCM; supply chain management; fuzzy AHP; analytical hierarchy process; disruptions; operational risks; disruption risks; risk management; risk mitigation; efficiency; resilience; linguistic evaluations; subjective evaluations; India; manufacturing industry; linguistic variables; numerical values; predefined scales; fuzziness; exact numbers; numerical intervals; weight; survey data; multicriteria decision making; MCDM.

DOI: 10.1504/IJMCDM.2012.045080

International Journal of Multicriteria Decision Making, 2012 Vol.2 No.1, pp.1 - 28

Available online: 24 Jan 2012 *

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