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International Journal of Fuzzy Systems

, Volume 18, Issue 6, pp 1141–1161 | Cite as

A Fuzzy Reverse Logistics Inventory System Integrating Economic Order/Production Quantity Models

  • Ehsan Shekarian
  • Ezutah Udoncy Olugu
  • Salwa Hanim Abdul-RashidEmail author
  • Eleonora Bottani
Article

Abstract

This paper develops a reverse inventory model where the recoverable manufacturing process is affected by the learning theory. We propose the inclusion of the fuzzy demand rate of the serviceable products and the fuzzy collection rate of the recoverable products from customers in the total cost function of the model. Two popular defuzzification methods, namely the signed distance technique, a ranking method for fuzzy numbers, and the graded mean integration representation method are employed to find the estimate of the total cost function per unit time in the fuzzy sense. We provide a comprehensive numerical example to illustrate and compare the results obtained by the two mentioned defuzzification methods. This is one of the only few attempts in the related literature comparing the performance of these methods with the effect of the fuzziness of both of the demand and the collection rate in the presence of the learning simultaneously. The results indicate that deciding on which method could be used depends on the target strategy that could focus on the total cost, ordering lot size, or recovery lot size.

Keywords

Fuzzy set theory Signed distance Graded mean integration representation Reverse logistics Inventory management Economic order/production quantity 

Notes

Acknowledgments

The first author wishes to express his gratitude to University of Malaya for funding his research (Grant No. RP018b-13aet).

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Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Ehsan Shekarian
    • 1
  • Ezutah Udoncy Olugu
    • 1
  • Salwa Hanim Abdul-Rashid
    • 1
    Email author
  • Eleonora Bottani
    • 2
  1. 1.Centre for Product Design and Manufacturing, Department of Mechanical Engineering, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Industrial EngineeringUniversity of ParmaParmaItaly

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