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Convergence time for the linkage learning genetic algorithm
Ying-ping Chen1, David E Goldberg
1Department of Computer Science, National Chiao Tung University, Hsinchu City 300, Taiwan. ypchen@csie.nctu.edu.tw
Abstract:
This paper identifies the sequential behavior of the linkage learning genetic algorithm, introduces the tightness time model for a single building block, and develops the connection between the sequential behavior and the tightness time model. By integrating the first-building-block model based on the sequential behavior, the tightness time model, and the connection between these two models, a convergence time model is constructed and empirically verified. The proposed convergence time model explains the exponentially growing time required by the linkage learning genetic algorithm when solving uniformly scaled problems.
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