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Dependency Structure Matrix Analysis: Offline Utility of the Dependency Structure Matrix Genetic Algorithm
Tian-Li Yu and David E. Goldberg
Illinois Genetic Algorithms Laboratory (IlliGAL), Department of General Engineering, University of Illinois at Urbana-Champaign, 104 S. Mathews Ave, Urbana, IL 61801tianliyu@illigal.ge.uiuc.edu
deg@illigal.ge.uiuc.edu
Abstract. This paper investigates the off-line use of the dependency structure matrix genetic algorithm (DSMGA). In particular, a problem-specific crossover operator is design by performing dependency structure matrix (DSM) analysis. The advantages and disadvantages of such an off-line use are discussed. Two schemes that helps the off-line usage are proposed. Finally, those off-line schemes are demonstrated by DSMGA on MaxTrap functions.
LNCS 3103, p. 355 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004