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A partially backlogged supply chain model for deteriorating items under reverse logistics, imperfect production/remanufacturing and inflation

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  • S.R. Singh
  • Swati Sharma

Abstract

Reverse logistics increasingly conquered interest in the past decade. It consists of operations related to the reuse of products, such as the collection of products from end users and general processes such as reusing, repairing, and recycling. In this paper, a reverse logistics supply chain inventory model in an inflationary environment is developed. Production and remanufacturing rates are finite and variable. During the production (remanufacturing) process some imperfect quality products are produced (remanufactured), which are reworked after production (remanufacturing) run. Items deteriorate over time with time-varying deterioration rate. Many classical reverse logistics supply chain models are developed with constant demand rate and ignoring the shortages which are not true all the time in practical life. Therefore, in this model, it is assumed that the demand rate of the buyer is a function of on-hand inventory and selling price. Shortages are allowed only for the buyer and partially backordered with a time-dependent backlogging rate. The purpose of this study is to determine the optimal integrated reverse logistics supply chain policy. Finally, numerical examples and sensitivity analysis along with some decision-making implications are provided.

Suggested Citation

  • S.R. Singh & Swati Sharma, 2019. "A partially backlogged supply chain model for deteriorating items under reverse logistics, imperfect production/remanufacturing and inflation," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 33(2), pages 221-255.
  • Handle: RePEc:ids:ijlsma:v:33:y:2019:i:2:p:221-255
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    Citations

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    Cited by:

    1. Sudip Adak & G. S. Mahapatra, 2021. "Effect of inspection and rework of probabilistic defective production on two-layer supply chain incorporating deterioration and reliability dependent demand," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 565-578, June.
    2. Dharmendra Yadav & Umesh Chand & Ruchi Goel & Biswajit Sarkar, 2023. "Smart Production System with Random Imperfect Process, Partial Backordering, and Deterioration in an Inflationary Environment," Mathematics, MDPI, vol. 11(2), pages 1-20, January.

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