Optimizing Firing Position Usage for Survivability and Effectiveness in Artillery Shoot-and-Scoot Tactics

In shoot-and-scoot tactics, a common rule is that artillery units should not reuse firing positions; a more cautious rule is that they should not even pass near an old firing position when relocating. We use the cautious rule to define a variant of the traveling salesman problem, where an artillery unit shall use as many firing positions as possible with minimal travel time and never reuse or pass near an old firing position. We develop greedy and randomized heuristic algorithms and test them on some examples, and an auxiliary algorithm that finds a lower bound of the travel time. We also use “independent sets” of graph theory to reduce a problem instance to one or several smaller instances. We find that one can get good solutions reasonably fast by running a randomized algorithm repeatedly and that problem reduction via independent sets can improve performance.