Abstract
As a function optimizer or a search procedure, GAs are very powerful and have some advantages. Fundamental research concerning the internal behavior of GAs has highlighted their limitations as regards search performances for what are called GA-hard problems. The reason for these difficulties seems to be that GAs generate insufficient strategies for the convergence of populations. To overcome this problem, an extended GA, which we name the filtering-GA, that adopts the method of changing the effect of the objective function on the dynamics of the GA, is proposed.
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© 1994 Springer-Verlag Berlin Heidelberg
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Sakanashi, H., Suzuki, K., Kakazu, Y. (1994). Controlling dynamics of GA through filtered evaluation function. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_268
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DOI: https://doi.org/10.1007/3-540-58484-6_268
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