Optimisation of Vehicle Routing Problem using Hyper-heuristics

The vehicle routing problem (VRP) is a computationally challenging combinatorial problem. It has been intensively studied by many researchers in the last sixty years. Due to the significant economic benefit that can be achieved by optimizing the routing problems in practice, more and more attention has been given to several extensions of the VRPs that arise in real life. These extensions are called Rich Vehicle Routing Problems (RVRPs). In contrast to traditional VRP that focuses on the idealized models with unrealistic assumptions, the research of RVRPs considers those complex constraints faced in real-life planning. It provides solutions that are executable in practice. This work takes a rich VRP problem combining a capacitated vehicle routing problem with time windows (CVRPTW) and a service technician routing and scheduling problem (STRSP); for delivering various equipment based on customers' requests and the subsequent installation by several technicians. The main goal is to reduce the overall costs of used resources and the total transportation costs of trucks/technicians. The problem was the topic of the fourth edition of the VeRoLog Solver Challenge in cooperation with the ORTEC company. The problem was solved in C++ by implementing three different Hyper-heuristic methods: SR-IE, SR-SA and SS-SA. These methods are compared, and SS-SA is found to have the best performance.