A Time-Indexed Generalized Vehicle Routing Model for Military Aircraft Mission Planning

Abstract

We introduce a time-indexed mixed integer linear programming model for a military aircraft mission planning problem, where a fleet of cooperating aircraft should attack a number of ground targets so that the expected effect is maximized. The model is a rich vehicle routing problem and the direct application of a general solver is only practical for scenarios of very moderate sizes. Therefore, a Dantzig–Wolfe decomposition and column generation approach is considered. A column here represents a specific sequence of tasks for one aircraft, and to generate columns, a longest path problem with side constraints is solved. We compare the column generation approach with the time-indexed model with respect to upper bounding quality and conclude that the Dantzig–Wolfe decomposition yields a much stronger formulation of the problem.