A constrained Nash bargaining approach to the stock rationing problem in multi-echelon supply chains

In order to survive in the global volatile market place, supply chain analysts are brainstorming to arrive at robust inventory control policies that prevents inventory worth of millions of dollars to get tied up in the chain and at the same time ensures to achieve the differentiated customer service levels. Inventory rationing is a useful strategy to tackle the above problem of conflicting objectives, i.e., minimizing inventory costs (holding costs and backorder costs) and achieving the desired customer service levels. In this paper, we consider a multi-echelon supply distribution system and pose the stock allocation problem in a constrained Nash bargaining (NB) setting. The objective of the model is to determine a set of rationing fractions at the central depot in order to minimize the order-up-to level inventory yet exactly achieving the differentiated target fill rates. It is our firm belief that the distribution resource planning (DRP) managers will find the proposed models a useful tool in their stock allocation decision-making process. Rigorous computational experiments suggests that our approach performs better than the existing ones for this important problem.