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This paper introduces a new heuristic algorithm that aims to solve the military route vulnerability problem, which involves assessing the vulnerability of military cargo flowing over roads and railways subject to enemy interdiction.

Graph theory, a heuristic and a binary integer program are used in this paper.

This work allows transportation analysts at the United States Transportation Command to identify a relatively small number of roads or railways that, if interdicted by an enemy, could disrupt the flow of military cargo within any theater of operation.

This research does not capture aspects of time, such as the reality that cargo requirements and enemy threats may fluctuate each day of the contingency.

This work provides military logistics planners and decision-makers with a vulnerability assessment of theater distribution routes, including insights into which specific roads and railways may require protection to ensure the successful delivery of cargo from ports of debarkation to final destinations.

This work merges network connectivity and flow characteristics with enemy threat assessments to identify militarily-useful roads and railways most vulnerable to enemy interdictions. A geographic combatant command recently used this specific research approach to support their request for rapid rail repair capability.

This paper aims to propose two solution approaches to determine the number of ground transport vehicles that are required to ensure the on-time delivery of military equipment between origin and destination node pairs in some geographic region, which is an important logistics problem at the US Transportation Command.

The author uses a mathematical program and a traditional heuristic to provide optimal and near-optimal solutions, respectively. The author also compares the approaches for random, small-scale problems to assess the quality and computational efficiency of the heuristic solution, and also uses the heuristic to solve a notional, large-scale problem typical of real problems.

This work helps analysts identify how many ground transport vehicles are needed to meet cargo delivery requirements in any military theater of operation.

This research assumes all problem data is deterministic, so it does not capture variations in requirements or transit times between nodes.

This work provides prescriptive details to military analysts and decision-makers in a timely manner. Prior to this work, insights for this type of problem were generated using time-consuming simulation taking about a week and often involving trial-and-error.

This research provides new methods to solve an important logistics problem. The heuristic presented in this paper was recently used to provide operational insights about ground vehicle requirements to support a geographic combatant command and to inform decisions for railcar recapitalization within the US Army.

This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo.

Supply chain network design, mixed integer programs, heuristics and regression are used in this paper.

This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements.

This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads.

This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space.

This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.