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Optimal Policy Structures of Stochastic Supply Chains with Outsourced Logistics Agreements


As evidenced by the rapid growth of the third-party logistics industry, more and more firms are electing to outsource logistics in order to cut costs and to focus on core competencies. One of the key decisions faced by firms when engaging third party logistics providers involves the nature of the agreement with the provider. Agreements range from requirements for service on demand to more structured agreements, in which the timing and size of shipment quantities are specified in advance. By agreeing to more structured arrangements, firms can decrease the uncertainty faced by the logistics provider and thus the logistics provider's costs, and therefore negotiate better rates. In order to understand the impact of using more structured agreements, however, firms need to understand how to effectively utilize the service provided in these agreements.

In this dissertation, motivated by these observations, we develop stylized models of simple production-distribution systems in order to explore the efficient use of structured logistics agreements. First, we introduce the general framework of models that we explore in this manuscript and present our motivation behind it. Second, we present a brief review of the stochastic supply chain literature. In this field, while there has been considerable interest in especially the supply contracts, the emphasis has been mostly on channel coordination and other informational efficiency aspects rather than the operational efficiency that we focus on. Third, we introduce our basic model with a fixed commitment logistics contract in a make-to-order production setting. We mathematically formulate this problem using stochastic dynamic programming and fully characterize the optimal policy structure. We prove some important properties of the optimal policy function that describe its sensitivity to reserved capacity levels and shipment times in the contract. We also provide sufficient conditions for decomposing this problem in time, whereby the complexity in computationally determining the optimal policy parameters can be greatly reduced. Fourth, we extend our model to a make-to-stock production environment and again completely characterize the structure of the optimal policy function. We show monotonicity of the optimal function parameters with respect to committed capacities in all cases and with respect to time in the periodic shipment case. Fifth, we analyze and extend our results regarding the optimal policy structure to more sophisticated logistics agreements such as option contracts and multi-level option contracts, and introduce additional uncertainties to the system such as stochastic spot market price and stochastic availability of additional capacity. Sixth, we present an initial analysis of the logistics agreements with shipment times chosen dynamically by the contact buyer. Lastly, we provide a computational study illustrating the sensitivity of optimal contract parameters to demand uncertainty and cost parameters, as well as exploring the relative benefits of different logistics agreements under varying operating conditions.

Overall, we investigate simplified models of production-distribution systems with outsourced logistics, our analysis and characterization of optimal policies provide some insight into the practical use of transportation contracts in addition to building a foundation for future investigation of models that incorporate more complicated critical aspects of important real-world problems relating to integrated production and distribution management in the presence of outsourced logistics agreements.

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