Algorithms for weapon target assignment and fire scheduling problem in planned artillery attack operations

Abstract

This dissertation focuses on scheduling problems arising in the military. In planned artillery attack operations, a large number of threatening enemy targets should be destroyed effectively to minimize fatal loss to the friendly forces. We consider a situation in which the number of available weapons is smaller than the number of targets and the available weapons are not identical. Therefore, it is required to develop new scheduling methodologies that coordinate heterogeneous weapon types to achieve specific objectives such as minimizing the latest completion time of firing operations (makespan) and minimizing total threat of the targets after engagement is finished. In this dissertation, we develop scheduling algorithms for the fire scheduling problem (FSP) with given assignment results, and then, we develop a methodology combining both assignment and scheduling decision for the entire planned artillery attack operation. First, we address the minimization of the makespan criterion for the FSP, in which the sequence of targets to be fired at is determined. In this environment, we assume that there are m available weapons to fire at n targets (>m) and the weapons are already allocated to targets. One target can be fired by not only a weapon but also multiple weapons, and these fire operations should start simultaneously regardless of the weapons while the finish time of them may be different. We develop several dominance properties and a lower bound for the problem, and suggest a branch and bound algorithm exploiting them. Also, we introduce several local search methods and compare the solutions with the optimal solutions obtained from the branch and bound algorithm. Secondly, we consider the situation in which targets may move and hence the probability that a target is destroyed by a firing attack decreases as time passes. We present a branch and bound algorithm for the FSP with the objective of minimizing total threat of the targets, which is expressed as a ...