Applying a fuzzy sets-based heuristic to the protein structure prediction problem

The interface between combinatorial optimization and fuzzy sets-based methodologies is the subject of very active and increasing research. In this context we describe FANS, a fuzzy adaptive neighborhood search optimization heuristic that uses a fuzzy valuation to qualify solutions and adapts its behavior as a function of the search state. FANS may also be regarded as a local search framework. We show the application of this fuzzy sets-based heuristic to the protein structure prediction problem in two aspects: first, to analyze how the codification of the solutions affects the results, and second, to confirm that FANS is able to obtain as good results as a genetic algorithm. Both results shed some light on the application of heuristics to the protein structure prediction problem and show the benefits and power of combining basic fuzzy sets ideas with heuristic techniques. (C) 2002 Wiley Periodicals, Inc.