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Applying a fuzzy sets‐based heuristic to the protein structure prediction problem
Author(s) -
Blanco Armando,
Pelta David A.,
Verdegay JoséL.
Publication year - 2002
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10042
Subject(s) - heuristics , fuzzy logic , heuristic , computer science , mathematical optimization , artificial intelligence , genetic algorithm , machine learning , mathematics
The interface between combinatorial optimization and fuzzy sets‐based methodologies is the subject ofvery active and increasing research. In this context we describe FANS, a fuzzy adaptive neighborhood searchoptimization heuristic that uses a fuzzy valuation to qualify solutions and adapts its behavior as a function ofthe 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 problemin two aspects: first, to analyze how the codification of the solutions affects the results, and second, toconfirm that FANS is able to obtain as good results as a genetic algorithm. Both results shed some light on theapplication of heuristics to the protein structure prediction problem and show the benefits and power ofcombining basic fuzzy sets ideas with heuristic techniques. © 2002 Wiley Periodicals, Inc.