Structure and metaheuristics

Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems. The reason for that, however, remains unclear. A framework for a theory of metaheuristics crucially depends on a formal representative model of such algorithms. This paper unifies/reconciles in a single framework the model of a black box algorithm coming from the no-free-lunch research (e.g. Wolpert et al. [25], Wegener [23]) with the study of fitness landscape. Both are important to the understanding of meta-heuristics, but they have so far been studied separately. The new model is a natural environment to study meta-heuristics. Categories and Subject Descriptors F.2 [Theory of Computation]: ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY General Terms Algorithms,Theory Keywords Theory, Representation, No Free Lunch, Heuristics

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Yossi Borenstein, Riccardo Poli
• Keywords: Difficult Combinatorial Optimization, Formal Representative Model, GECCO 2006, Metaheuristics, Optimization