USING DATA FARMING AND OPTIMIZATION TO ENABLE ANALYSIS OF CONCEPTS OF EMPLOYMENT FOR SURFACE CONNECTORS

Abstract

The Marine Corps requires models and tools to examine what mix of connectors is needed to deliver equipment, personnel, and supplies during or before the contact phase of a conflict. If hostilities ensue, the Marine Corps needs the capability to determine the optimal connector fleet and delivery schedule for those connectors to insert and sustain the distributed force. In 2019, the Operations Analysis Directorate, Combat Development & Integration, developed a Schedule Mixed Integer Program (S-MIP) that optimizes the delivery schedule for transporting a set of equipment from designated source points to demand points, given inputs such as connector quantities, speed, range, carrying capacity, ability to embark/debark at given ports (nodes), and sea state. As part of a Naval Research Program effort, NPS reviewed the original formulation and code and implemented improvements. This thesis supplements that effort by data farming the improved model to assess the impact of changes as well as to explore two solution strategies: single iteration and rolling horizon. We demonstrate that the improved model yielded a solution that delivered all serials in less time due to the more efficient use of decision variables, allowing for a greater number of previous decisions to be revisited using a rolling horizon. Further, the single iteration solve produced the solution with the lowest delivery time, and we therefore recommend continuing to experiment with this method.