Mohamed Elhassan Seliaman

Using Complete Squares Method to Optimize Replenishment Policies in a Four-Stage Supply Chain with Planned Backorders

We develop a four-stage, serial supply chain inventory model with planned backorders. This supply chain model is formulated for the integer multipliers coordination mechanism, where firms at the same stage of the supply chain use the same cycle time and the cycle time at each stage is an integer multiplier of the cycle time used at the adjacent downstream stage. We develop an optimal replenishment policy using a simple algebraic method to solve the problem without the use of differential calculus.

Optimizing the Two-Stage Supply Chain Inventory Model with Full Information Sharing and Two Backorders Costs Using Hybrid Geometric-Algebraic Method

We consider the case of a two-stage serial supply chain system. This supply chain system involves a single vendor who supplies a single buyer with a single product. The vendor’s production rate is assumed finite. In addition, the demand at the buyer is assumed deterministic. In order to coordinate their replenishment policies and jointly optimize their operational costs, the two supply chain partners fully share their relevant information. For this purpose, we develop an integrated inventory replenishment model assuming linear and fixed backorders costs. Then, we use a hybrid geometric-algebraic method to drive the optimal replenishment policy and the minimum supply chain total cost in a closed form.

Simulation Optimization of a Four-Stage Supply Chain System

Todays information technology allows firms to share inventory profiles and demand data quickly and inexpensively. In this paper, we develop a discrete-event simulation model for a four-stage supply chain. We assume that the four chain parties share their inventory and demand information. The performance measure that is used in the model to evaluate the system performance is expected total cost which consists of the inventory holding cost, the ordering cost, and the shortage cost. The simulation model is optimized using SimRunner optimization package

Algebraic modelling of a two level supply chain with defective items

M. Khan and M.Y. Jaber, Optimal inventory cycle in a two-stage supply chain incorporating imperfect items from suppliers. Int. J. Oper. Res. 10 (2011) 442–457, have addressed a two level supply chain of defective items. They compared three coordination mechanisms, i.e. cycle time; K –multiplier cycle time; and 2K –multiplier cycle time. This paper proposes a simpler algebraic solution for the K –multiplier cycle time mechanism without the use of differential calculus. The two level supply chain with defective items is illustrated with a numerical example. A sensitivity analysis is also provided.

Production and Inventory Decisions in a Multi-Stage Supply Chain with Transportation Cost

In this paper we consider the case of a three- stage supply where a firm can supply many customers. This supply chain system involves suppliers, manufactures, and retailers. Production and inventory decisions are made at the suppliers and manufactures levels. The production rates for the suppliers and manufactures are assumed finite. In addition the demand for each firm is assumed to be known. The problem is to coordinate production, inventory and transportation decisions across the supply chain so that the total cost of the system is minimized. For this purpose, we incorporate transportation cost explicitly into the model and describe optimal solution procedure for solving the model.

Simulation optimization of a supply chain with globally shared inventory profiles

We develop a discrete-event simulation model a three-stage supply chain consisting of a single product, a retailer, a distributor, and a factory. The factory it gets raw materials from an outside supplier, which is not included in this current model. Demand at the retailer follows a random distribution. The retailer carries inventory and replenishes his stock from the distributor according to a (s, S) policy; that is, when inventory position at the retailer reaches s, an order. The order size equals the difference between the inventory capacity S and the actual inventory level. We assume that excess demand is backordered at the retailer. When the retailer places an order, the distributor satisfies the full order immediately upon availability. If not enough stock is available the excess order is fully or partially backordered and hence will experience a random delay. Delayed retailer orders are satisfied on a first-come, first-served basis. In addition to the possible random delay at the distributor, the transit time from the supplier to the retailer is random. We also assume that the distributor has online information on the inventory status and demand activities of the retailer and replenishes his stock from a factory. The factory also has access to the distributor demand and inventory profiles. The factory follows the economic production quantity (EPQ) policy and he gets the material from an outside source.