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The Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is acombinatorial optimization problem of designing routes for vehicles to visitcustomers such that a cost function, typically the number of vehicles or thetotal travelled distance, is minimized. The CF-EVRP involves constraints suchas time windows on the delivery to the customers, limited operating range ofthe vehicles, and limited capacity on the number of vehicles that a roadsegment can simultaneously accommodate. In previous work, the compositionalalgorithm ComSat was introduced and that solves the CF-EVRP by breaking it downinto sub-problems and iteratively solve them to build an overall solution.Though ComSat showed good performance in general, some problems tooksignificant time to solve due to the high number of iterations required to findsolutions that satisfy the road segments' capacity constraints. The bottleneckis the Path Changing Problem, i.e., the sub-problem of finding a new set ofshortest paths to connect a subset of the customers, disregarding previouslyfound shortest paths. This paper presents an improved version of thePathsChanger function to solve the Path Changing Problem that exploits theunsatisfiable core, i.e., information on which constraints conflict, to guidethe search for feasible solutions. Experiments show faster convergence tofeasible solutions compared to the previous version of PathsChanger.

Leveraging Conflicting Constraints in Solving Vehicle Routing Problems