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Growing Science » Uncertain Supply Chain Management » A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment

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Uncertain Supply Chain Management

ISSN 2291-6830 (Online) - ISSN 2291-6822 (Print)
Quarterly Publication
Volume 4 Issue 2 pp. 107-122 , 2016

A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment Pages 107-122 Right click to download the paper Download PDF

Authors: Preeti Jawla, S. R. Singh

DOI: 10.5267/j.uscm.2015.12.001

Keywords: Exponential demand rate, Exponential holding cost, Imperfect production, Inflation, Learning, Multi-items, Preservation, Reverse logistics

Abstract: This paper presents a unified multi items general inventory model for integrated production of new items and remanufacturing of returned and defected items for a finite planning horizon. In this paper, a production model that takes into account learning, instantaneous deterioration rate and inflation is proposed. In addition, we also consider that the holding cost is a non-negative, non-decreasing and continuous function of time. In this model, the preservation technology is used to reduce the rate of product deterioration. A theory is developed to find the optimal solution of the proposed model; it is then exemplified with the help of several numerical examples. An efficient solution procedure is also provided to find the optimal strategy. Finally, sensitivity of the optimal solution to changes in the values of different parameters of the system and the convexities of the cost functions are also studied and represented through the graphs.

How to cite this paper
Jawla, P & Singh, S. (2016). A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment.Uncertain Supply Chain Management, 4(2), 107-122.

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Journal: Uncertain Supply Chain Management | Year: 2016 | Volume: 4 | Issue: 2 | Views: 2697 | Reviews: 0

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