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International Journal of Innovation and Scientific Research
ISSN: 2351-8014
 
 
Tuesday 15 October 2019

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Optimal Replenishment Policies for Two-Echelon Inventory Problems with Stationary Price and Stochastic Demand


Volume 13, Issue 1, January 2015, Pages 98–106

 Optimal Replenishment Policies for Two-Echelon Inventory Problems with Stationary Price and Stochastic Demand

Kizito Paul Mubiru

Original language: English

Received 29 October 2014

Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


Planning and managing replenishment policies of items plays an important role in supply chain management. In this paper, a new mathematical model is developed to optimize replenishment policies of a two-echelon inventory system under demand uncertainty. The system consists of one factory warehouse at the upper echelon and three supermarkets at the lower echelon. A special case of this model is where sales price and scheduled inventory replenishment periods are uniformly fixed over all echelons. Demand at the supermarkets is stochastic and stationary. Adopting a Markov decision process approach, the states of a Markov chain represent possible states of demand for milk powder product. The objective is to determine in each echelon of the planning horizon an optimal replenishment policy so that the long run sales revenue is maximized for a given state of demand. Using weekly equal intervals, the decisions of when to replenish additional units are made using dynamic programming over a finite period planning horizon. A numerical example demonstrates the existence of an optimal state-dependent replenishment policy and sales revenue over the echelons.

Author Keywords: Echelon, Inventory, Stationary price, Stochastic demand.


How to Cite this Article


Kizito Paul Mubiru, “Optimal Replenishment Policies for Two-Echelon Inventory Problems with Stationary Price and Stochastic Demand,” International Journal of Innovation and Scientific Research, vol. 13, no. 1, pp. 98–106, January 2015.