Wartime Logistics Model for Multi-support Unit Location-Allocation with Front Line Changes

Abstract

To reflect a realistic, changing front line, wartime logistics are illustrated by a dynamic location-allocation model. In this thesis, a mixed integer programming model is developed to decide the timing of unit relocation for continuous resupply, safe locations for support units, and delivery amounts that minimize total risk to the logistics service. Total risk in wartime logistics is represented by unsatisfied demand, hazard of support site, and the number of relocation. The proposed mixed integer programming model reflects realistic factors in battle situations, such as maximum distance, vehicle capacity, basic load carried by combat units, and limited supplies during unit relocation. Furthermore, special operators for crossover and mutation are developed to maintain feasibility of possible solutions, and an efficient hybrid genetic algorithm is proposed to find optimal and near-optimal solutions.