Genetic programming hyper-heuristic for multi-vehicle uncertain capacitated arc routing problem

Yi Mei, Mengjie Zhang

Abstract: This paper investigates evolving routing policy for general Uncertain Capacitated Arc Routing Problems (UCARP) with any number of vehicles, and for the first time, designs a novel model for online decision making (i.e. meta-algorithm) for multiple vehicles in service simultaneously. Then, we develop a GPHH based on the meta-algorithm. The experimental studies show the GPHH can evolve much better policies than the state-of-the-art manually designed policy. In addition, the reusability of the evolved policies dramatically decreases when the number of vehicles changes, which suggests a retraining process when a new vehicle is brought or an existing vehicle breaks down.