Evaluation of inventory replenishment policies on supply chain performance with grey relational analysis

Abstract

The objective of this paper is to evaluate various inventory position-based (IP-based) and non-inventory position-based (NIP-based) replenishment policies on the performance of a serial supply chain having four stages: manufacturer, distributor, wholesaler and retailer. The IP-based policies use inventory position-based information for replenishment whereas NIP-based policies do not require such information. The performance indicators are supply chain fill rate, bullwhip effect and total cost of supply chain. An experimental study is conducted using a simulation model under no information sharing and mean customer demand information sharing scenarios and the policies are ranked for each scenario using grey relational analysis. This analysis shows that the performance of the supply chain is better when NIP-based policies are used. The statistical analysis of the impact of information sharing among the supply chain members shows that the information sharing strategy has an impact on the performance of supply chain when IP-based policies are used.