Computational experiment of methods to determine periodic ( R , Q ) inventory policy parameters: a case study of information decentralised distribution network

This paper presents a case study of inventory management at distribution centre for hundreds of herbal products in Thailand. Differences in multiple products are characterised in terms of movement and demand variation. The incoming lead time from the manufacturer is time varying. The distribution network is information decentralised such that the distribution centres use replenishment orders from over 2,200 stores and hospitals to represent the end-customer demand. With the lack of real time inventory control system, the distribution centres implement a periodic (R, Q) policy for each item. The challenge is to properly set the parameters of the inventory policy for each product to minimise the total inventory management cost. Five methods with different degrees of computational requirement are implemented. An enumeration distribution is used to model the demand during varying lead time due to the lack of fits of widely used probability distributions. A computational experiment on the case study data is performed where method performance is evaluated through simulation. Statistical analysis of the results is conducted to identify the most effective methods to determine the inventory policy parameters.