This dissertation studies the management of operations that match surplus inventory of one party to meet the need of another. The first part is concerned with the efficient and robust design of transshipment networks in a commercial environment. The second part is concerned with a sequential resource allocation problem in a nonprofit distribution operation. For both topics, efficient design and control principles are determined. Transshipment, the sharing of inventory among parties at the same echelon level of a supply chain, can be used to reduce costs. The effectiveness of transshipment is in part determined by the configuration of the transshipment network. We introduce chain configurations in transshipment settings, where every party is linked in one connected loop. We show analytically that the chain configuration is superior to configurations suggested in the literature. In addition, we demonstrate the efficiency and robustness of chain configurations for more general scenarios. We extend our results to more general configurations and develop properties of low cost transshipment networks. We capture these properties in a metric to determine efficient and robust network configurations for transshipment. Additionally, we consider the problem of distributing a scarce resource to meet sequentially observed customer demand in a nonprofit setting. In a commercial setting, the amount distributed to each customer is determined to maximize profit; however, this objective may lead to inequitable distributions among customers. The alternate objectives that arise in nonprofit operations lead to new variations on traditional problems in operations research. We solve the sequential resource allocation problem with an objective function aimed at equity and sustainability. We define service in terms of fill rate, the ratio of the distribution amount to demand, and develop an objective function to maximize the minimum fill rate among customers. Through a dynamic programming framework, we characterize the structure of the optimal allocation policy for a given sequence of customers. In addition, we address the problem of customer visitation sequence by identifying properties to consider in making sequencing decisions to maximize the objective. For both inventory distribution and customer sequencing decisions, we develop heuristic methods which yield near-optimal solutions.

Last modified

• 09/08/2018

Creator

• Robert W Lien

DOI

• https://doi.org/10.21985/N2873J

Subject

• Industrial Engineering and Management Sciences

Keyword

• Sequential Resource Allocation
• Transshipments
• Inventory Management

Date created

• 2008-05-08

Resource type

• Dissertation

Rights statement

• In Copyright