A general purpose Hyper – Heuristic based on Ant colony optimization

In the plan of the CHESC2001 competition [1], an hyper heuristic has been designed based on the Ant Colony Optimization method (from now ACO). According to the competition goals, the algorithm was developed with the intention to produce an independent model of the problem domain and the particular instance to be solved. This means that the hyper-heuristic is abstracted from the features of each heuristic previously known; therefore, the work is based exclusively on the behavior observed during the problem resolution. These types of hyper-heuristics are known as heuristic selection and online learning [2]. The model presented in this document was implemented for Hyflex framework [3] provided for the participatants in the competition.