ABSTRACT
Due to the large amount of money engaged with inventory along supply chains, especially with inventory holding costs, it is extremely important to employ a good inventory policy in order to meet the customer demand without delays. This paper presents a vendor-managed inventory policy with emergency orders, for a supply chain which consists of a single vendor and a single retailer where the retailer faces Poisson customer demand. Two mathematical models were developed using two approaches. Approach 1 used the concept of demand rate while approach 2 is based on total demand received during the cycle. The formulated models are used to determine the optimal base stock level, delivery quantity to the retailer and cycle length such that the total expected inventory cost is minimized. Numerical experiments and sensitivity analysis were conducted to examine the behavior of the optimal solution and provide general guidelines and implications.
Disclosure Statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Jayalal Wettasinghe
Jayalal Wettasinghe is a Senior Lecturer in department of Mechanical and Manufacturing Technology of University of Vocational Technology, Sri Lanka. He received a PhD in Industrial and Manufacturing Engineering from School of Engineering and Technology of Asian Institute of Technology, Thailand in 2018. His research interests include inventory optimization in supply chains and application of operational research in industrial problems.
Huynh Trung Luong
Huynh Trung Luong is an Associate Professor in department of Industrial Systems Engineering, School of Engineering and Technology, Asian Institute of Technology, Thailand. He received a D.Eng from School of Engineering and Technology of Asian Institute of Technology, Thailand in 2000. His research interests include establishment of emergency inventory policies and inventory policies for perishable products, supply chain design and measures of bullwhip effect in supply chains, availability-based and reliability-based maintenance, fuzzy quality control charts, statistical design of experiments, and network flows related problems.