An Exact Algorithm for a Fuel-Constrained Autonomous Vehicle Path Planning Problem
For operations researchers and autonomous vehicle logistics planners, this provides exact solutions to a complex routing problem with fuel constraints, though it is an incremental extension of existing vehicle routing formulations.
The paper tackles a fuel-constrained path planning problem for autonomous vehicles with refueling stations, presenting four MILP formulations and a branch-and-cut algorithm that computes optimal solutions for instances with up to 30 targets and 5 vehicles.
This paper addresses a fuel-constrained, autonomous vehicle path planning problem in the presence of multiple refueling stations. We are given a set of targets, a set of refueling stations, and a depot where $m$ vehicles are stationed. The vehicles are allowed to refuel at any refueling station, and the objective of the problem is to determine a route for each vehicle starting and terminating at the depot, such that each target is visited by at least one vehicle, the vehicles never run out of fuel while traversing their routes, and the total travel cost of all the routes is a minimum. We present four new mixed-integer linear programming formulations for the problem. These formulations are compared both analytically and empirically, and a branch-and-cut algorithm is developed to compute an optimal solution. Extensive computational results on a large class of test instances that corroborate the effectiveness of the algorithm are also presented.