This paper presents a hybrid Decision Support System (DSS) for slow moving spare parts joint replenishment in a nuclear power plant. In this study, we integrate the fuzzy and grey theory-based spare parts criticality class evaluation model to confirm the target service level, and the web-based joint replenishment DSS to obtain reasonable purchase parameters that can be helpful for reducing tota...

We consider the one-warehouse multiple retailer inventory model with a submodular joint setup cost function. The objective of this model is to determine an inventory replenishment policy that minimizes the long-run average system cost over an infinite time horizon. Although the optimal policy for this problem is still unknown, a class of easy-to-implement power-of-two policies are 98% effective...

Decision making plays an important role in economics, psychology, philosophy, mathematics, statistics and many other fields. In each field, decision making consists of identifying the values, uncertainties and other issues that define the decision. In any field, the nature of the decisions is affected by environmental characteristics. In this paper, we are considered the production planning pro...

This paper presents a study of solving the joint replenishment problem (JRP) by using the RAND method, a heuristic approach that has been proven to find almost as good as optimal solutions, under uncertain customer demands and inaccurate unit holding cost estimation. The classical JRP deals with the issue of determining a replenishment policy that minimizes the total cost of replenishing multip...

We study the stochastic machine replenishment problem, which is a canonical special case of closed multiclass queuing systems in Markov decision theory. The problem models the scheduling of processor repairs in a multiprocessor system in which one repair can be made at a time and the goal is to maximize system utilization. We analyze the performance of a natural greedy index policy for this pro...

The joint replenishment problem (JRP) has received considerable attention and all of the work on JRP is under explicit environment. In fact, the decision makers often have to face vague operational conditions. In this paper, a novel JRP model with fuzzy minor replenishment cost and fuzzy inventory holding cost is developed. More concisely, this model is a fuzzy dependent-chance programming (DCP...

Joint replenishment problem (JRP) is a common real problem which aims to minimize order cost and inventory holding cost. In this paper, classical, centralized and decentralized JRP models are discussed. An innovative heuristic to minimize the total cost is implemented for each model. This heuristic seeks to balance the order cost and the inventory holding costs. The results show that the innova...

In this paper we consider the problem of maximizing a separable concave function over a polymatroid. More specifically, we study the submodularity of its optimal objective value in the parameters of the objective function. This question is interesting in its own right and is encountered in many applications. But our research has been mainly motivated by a cooperative game associated with the we...

We consider the jointly replenishing N identical firms that operate under an EOQ like setting using a non-cooperative game. In this game, each firm bids how much it is willing to pay per unit of its replenishment and a service provider determines the frequency of the joint orders. We characterize the equilibrium under full and asymmetric information.

In practice, demands for items are often correlated with each other because of cross-selling effects. Traditional inventory models hold the assumption that demands are independent, which may lead to the risk of misestimating the inventory cost of associated items. This paper addresses a multi-item inventory system where demands for some minor items are correlated with that for a major item. Bec...