A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment

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.

Optimal decision problem in a three-level closed-loop supply chain with risk-averse players under demand uncertainty

“…Chen et al (2016) studied optimal replenishment quantity for new products and return rate of used products. Jawla & Singh (2016) considered a reverse logistics inventory model for integrated production of new items and remanufacturing of returned items. Weraikat et al (2016) studied the reverse chain of the pharmaceutical industry.…”

Optimal Production Policy for Imperfect Items Under Learning and Forgetting Environment

“…Jabber and Bonney (2003) developed a lot sizing model with learning forgetting in set-ups. Jawla and Singh (2016) developed an inventory model with imperfect production, for deteriorating items under learning and inflationary environment. Sepehri (2021) presented a productioninventory paradigm with imperfect quality that is supported by investments in quality enhancement and preservation technologies.…”

Fuzzy reverse logistics inventory model of smart items with two warehouses of a retailer considering carbon emissions

“…Simultaneously, Saxena et al [2] analyzed a remanufacturing inventory model base for the primary and secondary markets. Jawla and Singh [3] examined in reverse logistics model with the influence of inflation. After that, Ullah et al [4] examined an optimal remanufacturing system and reusable packaging capacity for single and multi-retailer closed-loop supply chain models under stochastic demand and return rate.…”