Selection Hyper-Heuristic Using a Portfolio of Derivative Heuristics

Generally, we distinguish between two classes of hyper-heuristic approaches, heuristic selection and heuristic generation. The former one works with existing heuristics and tries to find their optimal order for solving the instance. The later approach automatically generates new heuristic. Here, these two approaches are combined so that, first, a number of various heuristics are derived from a limited set of pre-existing heuristics for the selected optimization problem with regard to the diversity among the heuristics. Then, the heuristic selection approach is used to find the optimal sequence of heuristics leading to the best solution. Proof-of-concept experiments on the Capacitated Vehicle Routing Problem were carried out with the well-known Clarke-Wright, Mole-Jameson and Kilby constructive heuristics. Results show that the derived heuristics produce consistently better results than the original ones.