Efficient optimization of the dual-index policy using Markov chains

3We consider the inventory control of a single product in one location with two supply sources facing stochastic demand. A premium is paid for each product ordered from the faster `emergency' supply source. Unsatistfied emand is backordered and ordering decisions are made periodically. The optimal control policy for this system is known to be complex. For this reason we study a type of base-stock policy known as the dual-index policy (DIP) as control mechanism for this inventory system. Under this policy ordering decisions are based on a regular and an emergency inventory position and their corresponding order-up-to-levels. Previous work on this policy assumes deterministic lead times and uses simulation to and their optimal order-up-to levels. We provide an alternate proof for the result that separates the optimization of the DIP in two one-dimensional problems. An insight from this proof allows us to generalize the model to accommodate stochastic regular lead times and provide an approximate evaluation method based on limiting results so that optimization can be done without simulation. An extensive numerical study shows that this approach yields excellent results for deterministic lead times and good results for stochastic lead times

A Pre Review On The Interaction Component In Formulating Sustainable Supply Chain Management

The purpose of this paper is to explore the basic interaction components in formulating sustainable supply chain management. Sustainable Supply Chain is one of the advance technology approaches that compete with high productivity and less cost. In order, to achieve best performance on sustainability, the process of Supply Chain Management must accomplish and through with the management of industry. Process of Supply Chain Management includes five elements, which are; planning, procurement, production, delivery and response level. All the processes have their own interaction on manufacturing. The interaction framework in this paper can be used by manufacturers and researchers to gain more understanding on process of sustainable supply chain management

Expediting in Two-Echelon Spare Parts Inventory Systems

We consider a two-echelon spare parts inventory system consisting of one central warehouse and multiple local warehouses. Each warehouse keeps multiple types of repairable parts to maintain several types of capital goods. The local warehouses face Poisson demand and are replenished by the central warehouse. We assume that unsatisfied demand is backordered at all warehouses. Furthermore, we assume deterministic lead times for the replenishments of the local warehouses. The repair shop at the central warehouse has two repair options for each repairable part: a regular repair option and an expedited repair option. Both repair options have stochastic lead times. Irrespective of the repair option, each repairable part uses a certain resource for its repair. Assuming a dual-index policy at the central warehouse and base stock control at the local warehouses, an exact and efficient evaluation procedure for a given control policy is formulated. To find an optimal control policy, we look at the minimization of total investment costs under constraints on both the aggregate mean number of backorders per capital good type and the aggregate mean fraction of repairs that are expedited per repair resource. For this non-linear non-convex integer programming problem, we develop a greedy heuristic and an algorithm based on decomposition and column generation. Both solution approaches perform very well with average optimality gaps of 1.56 and 0.23 percent, respectively, across a large test bed of industrial size. Based on a case study at Netherlands Railways, we show how managers can significantly reduce the investment in repairable spare parts when dynamic repair policies are leveraged to prioritize repair of parts whose inventory is critically low

Real-time Allocation Decisions in Multi-echelon Inventory Control

Inventory control is a crucial activity for many companies. Given the recent advances in information technology, there have never been greater opportunities for coordinated inventory control across supply chain facilities. But how do we design efficient control methods and policies that take advantage of the detailed information that is now becoming available? This doctoral thesis investigates these issues within the field of inventory control theory. The objective of the research is: To develop mathematical models and policies for efficient control and increased understanding of stochastic multi-echelon inventory systems, with a focus on allocation decisions and the use of real-time information. This thesis is based on five scientific papers which are preceded by a summarizing introduction. The papers address different types of inventory distribution systems, all consisting of a central stocking facility that supplies an arbitrary number of local stocking facilities (referred to as retailers). The retailers face stochastic end customer demand. The systems are characterized by the presence of real-time inventory information, including continuously updated information on the current inventory levels at different facilities and on the locations of outstanding orders. In Paper I and Paper II we derive and evaluate different decision rules for stock allocation (known as allocation policies) for a central warehouse which applies a time based shipment consolidation strategy. The allocation policy determines how the central warehouse should distribute its stock among different retailers in case of shortages. New allocation policies that utilize real-time information are compared to the commonly used First Come - First Served policy which requires less information. In Paper III we shift focus to the delivery policy at a central warehouse which supplies multiple retailers that order in batches. When the central warehouse cannot satisfy an entire retailer order immediately, the delivery policy determines if the order should be shipped in several parts or in its entirety when all items are available. We investigate the value of using a new delivery policy that uses real-time information on when replenishments will arrive at the central warehouse. The information is used to determine the best course of action for each order placed by the retailers. We also study how to allocate safety stocks to all facilities in the system given this new policy. In Paper IV and Paper V we consider a system where retailers may receive emergency shipments from a support warehouse in combination with regular replenishments from a central warehouse/outside supplier. We investigate how safety stocks should be allocated between the retailers and the support warehouse. Furthermore, we evaluate the benefits of tracking orders in real time and using this information in the decision whether or not to request an emergency shipment

Financial Credit Risk Evaluation Based on Core Enterprise Supply Chains

Supply chain finance has broken through traditional credit modes and advanced rapidly as a creative financial business discipline. Core enterprises have played a critical role in the credit enhancement of supply chain finance. Through the analysis of core enterprise credit risks in supply chain finance, by means of a “fuzzy analytical hierarchy process” (FAHP), the paper constructs a supply chain financial credit risk evaluation system, making quantitative measurements and evaluation of core enterprise credit risk. This enables enterprises to take measures to control credit risk, thereby promoting the healthy development of supply chain finance

Performance evaluation of a two-echelon inventory system with network lost sales

peer reviewe