An ordering policy for deteriorating items with price-dependent iso-elastic demand under permissible delay in payments and price inflation

IF 1.8 4区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Mathematical and Computer Modelling of Dynamical Systems Pub Date : 2019-10-29 DOI:10.1080/13873954.2019.1677724
Puspita Mahata, G. C. Mahata, Avik Mukherjee
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引用次数: 24

Abstract

ABSTRACT This paper considers the problem of dynamic decision-making for an inventory model for deteriorating items under price inflation and permissible delay in payment. In this paper, we adopt an iso-elastic and selling price dependent demand function to model the finite time horizon inventory for deteriorating items. The stocks deteriorate physically at a constant fraction of the on-hand inventory. The objective of this paper is to determine the optimal retail price, number of replenishments, and the cycle time under two different credit periods so that the net profit is maximized. We discuss the optimization properties and develop an algorithm for solving the problem based on dynamic programming techniques. Numerical examples are presented to illustrate the validity of the optimal control policy, and sensitivity analysis on major parameters is performed to provide more managerial insights into deteriorating items.
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在允许的付款延迟和价格膨胀条件下,具有价格依赖等弹性需求的变质物品的订货策略
摘要本文研究了在价格上涨和允许延迟付款条件下,变质物品库存模型的动态决策问题。在本文中,我们采用了一个等弹性和销售价格相关的需求函数来对变质物品的有限时域库存进行建模。库存在物理上以现有库存的恒定比例恶化。本文的目的是确定两个不同信用期下的最优零售价格、补货次数和周期时间,以使净利润最大化。我们讨论了优化性质,并基于动态规划技术开发了一种求解该问题的算法。通过算例说明了最优控制策略的有效性,并对主要参数进行了敏感性分析,为劣化项目提供了更多的管理见解。
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来源期刊
CiteScore
3.80
自引率
5.30%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.
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