An EOQ model for non-instantaneous deteriorating items with time-dependent demand under partial backlogging

IF 3.6 2区 管理学 Q2 BUSINESS
R. Udayakumar
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引用次数: 0

Abstract

This article discusses an economic order quantity model for non-instantaneous deteriorating items in which the demand is assumed to be a linear function of time over an infinite planning horizon. In addition, the salvage value associated with the deteriorated units is also considered. The shortages are allowed and partially backlogged. A mathematical model is framed to obtain the replenishment policy which aids the retailer to minimize the total inventory cost. The objective of this work is to minimize the total inventory cost and to find the optimal length of replenishment and the optimal order quantity. The theory developed in this article is illustrated using numerical examples. A computational algorithm is designed to find the optimal solution. Sensitivity analysis is carried out to study the changes in the effect on the optimal solutions and some managerial insights are obtained.

部分积压条件下需求随时间变化的非瞬时变质物品EOQ模型
本文讨论了非瞬时变质物品的经济订货量模型,该模型假定需求是无限规划范围内时间的线性函数。此外,还考虑了与恶化单位有关的残值。短缺是允许的,并且部分积压。建立了一个数学模型,得到了帮助零售商使总库存成本最小化的补货策略。该工作的目标是最小化总库存成本,找出最优补货时间和最优订货量。本文提出的理论是用数值例子来说明的。设计了一种求最优解的计算算法。通过敏感性分析研究了影响最优解的变化,获得了一些管理启示。
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来源期刊
Journal of Management Analytics
Journal of Management Analytics SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
13.30
自引率
3.40%
发文量
14
期刊介绍: The Journal of Management Analytics (JMA) is dedicated to advancing the theory and application of data analytics in traditional business fields. It focuses on the intersection of data analytics with key disciplines such as accounting, finance, management, marketing, production/operations management, and supply chain management. JMA is particularly interested in research that explores the interface between data analytics and these business areas. The journal welcomes studies employing a range of research methods, including empirical research, big data analytics, data science, operations research, management science, decision science, and simulation modeling.
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