Designing reusable metaheuristic methods: A semi-automated approach

Many interesting optimization problems cannot be solved efficiently. Recently, a lot of work has been done on meta-heuristic optimization methods that quickly find approximate solutions to otherwise intractable problems. While successful, the field suffers from a notable lack of reuse of methods, both in practical applications as in research. In this paper, we describe a semi-automated approach to design more re-usable methods, based on key principles of re-usability such as simplicity, modularity and generality. We illustrate this methodology by designing general metaheuristics (using hyperheuristics) and show that the methods obtained are competitive with the contestants of the Cross-Domain Heuristic Search Competition (2011). In particular, we find a method performing better than the competition´s winner, which can be considered the state-of-the-art in domain-independent metaheuristic search.