The United States Coast Guard (USCG), now part of the Department of Homeland Security, has the mission to secure the U.S. coastline using a combination of air and sea capabilities. This paper focuses on an application of operations research techniques at the USCG to improve the performance of its aircraft service parts supply chain. We focused on evaluating the supply chain benefits from linking the aircraft maintenance database with the aircraft parts inventory database. This required us to (a) develop an approach to link the databases and (b) use aircraft maintenance information to improve the inventory management of service parts at the USCG. We first used mathematical programming tools to merge the maintenance database with the demand database. We then developed state-dependent supply replenishment policies that use part-age information to manage the service parts supply chain. We show that one of the proposed policies permits analytic estimation of the benefits of linking the data sets. The impact of these inventory policies was evaluated using empirical demand data for 41 critical parts over a five-year period. Computational results suggest that our proposed policies can lead to significant reductions in inventory cost over the current system, as high as 70% for some parts. Based on the insights from this study, the USCG is currently contracting with commercial vendors to develop an operational database and decision-support implementation across all parts.
T he problem of sharing manufacturing, inventory, or capacity to improve performance is applicable in many decentralized operational contexts. However, the solution of such problems commonly requires an intermediary or a broker to manage information security concerns of individual participants. Our goal is to examine use of cryptographic techniques to attain the same result without the use of a broker. To illustrate this approach, we focus on a problem faced by independent trucking companies that have separate pick-up and delivery tasks and wish to identify potential efficiency-enhancing task swaps while limiting the information they must reveal to identify these swaps. We present an algorithm that finds opportunities to swap loads without revealing any information except the loads swapped, along with proofs of the security of the protocol. We also show that it is incentive compatible for each company to correctly follow the protocol as well as provide their true data. We apply this algorithm to an empirical data set from a large transportation company and present results that suggest significant opportunities to improve efficiency through Pareto improving swaps. This paper thus uses cryptographic arguments in an operations management problem context to show how an algorithm can be proven incentive compatible as well as demonstrate the potential value of its use on an empirical data set.
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