Supply Chain Optimization for Threat Elimination in Contested Environment
Abstract
Having adequate supply of fuel, ammunition, weapons, food, and water is critical to being effective in contested environments. Makin,g good operational supply chain decisions, including where to send supply units and how much of which re,units, is thus necessary for maximal military success. At the same time, making high-quality operational supply chain decisions quic,kly and consistently is difficult, requiring one to consider many types temporally and spatially interconnected decisions. While exp,erienced practitioners may be able to make near-optimal decisions with minimal decision support, it can be difficult to achieve a hi,gh standard consistently and the task becomes more daunting as the operations get more and more complex. In addition to the inherent, complexity of their own, supply chain decisions interact with decisions about the design of military missions and the use of resour,ces against targets. For example, if a target is susceptible to an amply-supplied lower-value weapon, then it may make sense to desi,gn missions against that target to conserve more scarcely-supplied higher-value weapons. Thus, those designing missions against targ,ets need to have visibility into the capacity of the supply chain to transport resources, the value that these resources would have,if deployed elsewhere, and to take these considerations into account when making decisions. This level of coordination can be diffic,ult to achieve without sophisticated decision support.In this proposal, we focus on building mathematical optimization models capabl,e of overcoming these challenges and supporting consistent, high-quality supply chain decisions that are coordinated with mission de,sign. We specifically consider building and operating supply chains in support of threat elimination missions. An existing ONR-funde,d effort, led by Dr. Jeff Linderoth at University of Wisconsin, develops mathematical optimization models for threat elimination mis,eat elimination models, providing the flow of supply necessary for threat elimination activities.We will use mixed integer linear pr,ogramming (MILP) models and open-source solvers to develop a collection of software tools that can be used for making supply chain d,ecisions. Our starting point is a monolithic ?joint? formulation, in which supply chain and threat elimination is considered jointly, in a single MILP. At a high-level, this model can be viewed as the current threat elimination model augmented with supply chain dec,isions. The joint model is likely to be unwieldy and to require a host of additions and modifications on the existing threat elimina,el into two separate problems, one focused on supply chain operations and the other focused on mission design for threat elimination,.These supply chain and threat elimination problems are coordinated through a set of ?prices? that have a natural economic interpret,ation, expressing the value of resources as a function of time and location. The threat elimination problem that arises in this deco,mposition approach is almost exactly the same problem in the existing threat elimination work led by Dr. Linderoth, except that the,objective function needs to be slightly modified to accommodate resource prices. Thus, we will be able to coordinate supply chain an,d threat elimination models with minimal impact on the current threat elimination work. If incorporating uncertainty is deemed criti,cal, our approach has a pathway to incorporate uncertainty. We also plan on developing a simulator to test our model environments th,at are richer than those that can be captured in an optimization framework.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 08, 2022
- Source ID
- N000142212763
Entities
People
- Peter Frazier
Organizations
- Cornell University
- Office of Naval Research
- United States Navy