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Abstract: In real-coded genetic algorithms, some crossover operators do not work well on functions which have their optimum at the corner of the search space. To cope with this problem, we have a proposed boundary extension methods which allows individuals to be located within a limited space beyond the boundary of the search space. In this paper, we give an analysis of the boundary extension methods from the view point of sampling bias and perform a comparative study on the effect of applying two... (Update)
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BibTeX entry: (Update)
@misc{ and-search,
author = "Shigeyoshi Tsutsui And",
title = "Search Space Boundary Extension Method in Real-Coded Genetic Algorithms",
url = "citeseer.ist.psu.edu/405101.html" }
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