Abstract
In today’s fast-paced and competitive market place, organizations need every edge available to them to ensure success in planning and managing inventory of items with demand uncertainty. In such an effort, cost effective methods in determining optimal replenishment policies are paramount. In this paper, a mathematical model is proposed that optimize inventory replenishment policies of a periodic review inventory system under stochastic demand; with particular focus on malaria drugs in Ugandan pharmacies. Adopting a Markov decision process approach, the states of a Markov chain represent possible states of demand for drugs that treat malaria. Using weekly equal intervals, the decisions of whether or not to replenish additional units of drugs were made using discrete time Markov chains and dynamic programming over a finite period planning horizon. Empirical data was collected from two pharmacies in Uganda. The customer transactions of drugs were taken on a weekly basis; where data collected was analyzed and tested to establish the optimal replenishment policy and inventory costs of drugs. Results from the study indicated the existence of an optimal state-dependent replenishment policy and inventory costs of drugs at the respective pharmacies.
Highlights
Joint replenishment inventory decisions are common in business enterprises and various models have been developed to support this function
A novel approach that handles the inventory problem in the pharmaceutical supply chain (Candan and Yazgan, 2016) establish a demand-driven classical supply chain model and shows its effectiveness using an experimental study that consists of two different supply chain policies
Suppose one is interested in determining an optimal course of action at pharmacy P, namely to replenish additional units of drug d or not to replenish additional units of drug d during each time period over the planning horizon, where R is a binary decision variable
Summary
Joint replenishment inventory decisions are common in business enterprises and various models have been developed to support this function. Hospital logistics must be improved by coordinating procurement and distribution operations while respecting inventory capacities (Lappiere and Luiz, 2007) where emphasis is put on scheduling decisions: when to buy and deliver products at pharmacies, when each employee should work and what task he should do. This is a great challenge when demand for drugs in pharmacies follows a stochastic trend. The paper is organized as follows: After reviewing the previous work done, a mathematical model is proposed where initial consideration is given to the process of estimating model parameters.
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