PERFORMANCE APPRAISAL OF REVERSE LOGISTICS USING INTERVAL-VALUED FUZZY NUMBERS SET

Authors

  • Nitin Kumar Sahu Department of Mechanical Engineering, National Institute of Technology, Rourkela, Orissa-769008, India
  • Saurav Datta Department of Mechanical Engineering, National Institute of Technology, Rourkela, Orissa-769008, India
  • Siba Sankar Mahapatra Department of Mechanical Engineering, National Institute of Technology, Rourkela, Orissa-769008, India

Keywords:

Reverse Logistics, Interval-Valued (IV) Fuzzy Numbers Set

Abstract

Reverse logistics (RL) is the process of moving goods from their typical final destination for the purpose of capturing value, or proper disposal. Reverse logistics also includes processing returned merchandise due to damage, seasonal inventory, restock, salvage, recalls, and excess inventory. It also includes recycling programs, hazardous material programs, obsolete equipment disposition, and asset recovery. In relation to reverse supply chain management, reverse logistics performance appraisal is highly essential. To this end, the present paper presents a fuzzy based RL performance appraisal platform, applied in a case study. Interval-Valued Fuzzy Numbers Set (IVFNS) has been explored here to facilitate such a decision-modeling.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Yellepeddi S S (2006), “A Methodology for Evaluating the Performance of Reverse Supply Chains in Consumer Electronics Industry”, PhD Thesis, The University of Texas at Arlington.

Panousopoulou, Pagonaa, Papadopoulou Eleni- Mariab, and Manthou Vickyc, (2011), “Reverse Logistics Performance Indicators: A Conceptual Framework for Evaluating Reverse Logistics Services”, Annual Conference on Innovations in Business & Management London, The Center for Innovations in Business and Management Practice, pp. 1-3.

Amy J C, Trappey, Chang-Ru Wu, Charles V Trappey and Fu-Chiang Hsu (2009), “Using Fuzzy Cognitive Map for Evaluation of RFID-based Reverse Logistics Services”, Proceedings of the 2009 IEEE International Conference on Systems. San Antonio, USA.

Gülfem T, Bahadır G and Şule Ö (2011), “A Methodology for the Strategic Design of Reverse Logistics Networks and its Application in the Turkish White Goods Industry”, International Journal of Production Research, Vol. 49, 4543-4571.

Ezutah Udoncy Olugu and Kuan Yew Wong (2011), “Fuzzy Logic Evaluation of Reverse Logistics Performance in the Automotive Industry”, Scientific Research and Essays, Vol. 6, 1639-1649.

Arun K, Vasantha Geethan S Jose and Sunil Chandar C (2011), “Methodology for Performance Evaluation of Reverse Supply Chain”, International Journal of Engineering and Technology, Vol. 3, 213-224.

Wang G and Li X (1998), “The Applications of Interval-Valued Fuzzy Numbers and Interval-Distribution Numbers”, Fuzzy Sets Systems, Vol. 98, 331–335.

Chen S J (2006), “A New Method for Handling the Similarity Measure Problems of Interval-Valued Fuzzy Numbers”, In Proceedings of the Second International Conference on Natural Computation and the Third International Conference on Fuzzy Systems and Knowledge Discovery, Xi’an China, pp. 325–334.

Ting-Yu Chen and Hung-Lin Lai (2011), “A Risk Management Method for Enhancing Patient Safety Based on Interval-Valued Fuzzy Numbers”, African Journal of Business Management, Vol. 5, 11925-11945.

Chen S M (1995), “Arithmetic Operations between Vague Sets”, In Proceeding of International Joint Conference of CFSA/TFIS/SOFT ’95 on Fuzzy Theory and Applications, Taipei Taiwan, Republic of China, pp. 206–211.

Wei S H and Chen S M (2009), “Fuzzy Risk Analysis Based on Interval-Valued Fuzzy Numbers”, Expert Systems with Applications, Vol. 36, 2285–2299.

Ching-Torng Lin, Hero Chiub and Po-Young Chub, (2006), “Agility Index in the Supply Chain”, International Journal of Production Economics, Vol. 100, 285–299.

Sepulveda R, Castillo O, Melin P, Rodriguez-Diaz A and Montiel O (2007), “Experimental Study of Intelligent Controllers Under Uncertainty using Type-1 and Type-2 Fuzzy Logic”, International Journal of Information Sciences, Vol. 177, 2023–2048.

Zadeh L A (1975), “The Concept of a Linguistic Variable and its Application to Approximate Reasoning”, International Journal of Information Sciences, Vol. 8, 199–249.

Downloads

Published

2012-09-01

How to Cite

[1]
Nitin Kumar Sahu, Saurav Datta, and Siba Sankar Mahapatra, “PERFORMANCE APPRAISAL OF REVERSE LOGISTICS USING INTERVAL-VALUED FUZZY NUMBERS SET”, JME, vol. 7, no. 3, pp. 146–151, Sep. 2012.