Abstract
Many of the studies on GAs give emphasis on finding the global optimal solution. In this paper, we propose a new method which extend the application of GAs to domains that require detection of robust solutions. If a global optimal solution found is on a sharp-pointed location, there may be cases where it is not good to use this solution. In nature, the phenotypic feature of an organism is determined from the genotypic code of genes in the chromosome. During this process, there may be some perturbations. Let X be the phenotypic parameter vector, f(X) a fitness function and δ a noise vector. As can be easily understood from the analogy of nature, actual fitness function should be of the form f(X+δ). We use this analogy for the present work. Simulation results confirm the utility of this approach in finding robust solutions.
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Tsutsui, S., Ghosh, A., Fujimoto, Y. (1996). A robust solution searching scheme in genetic search. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1018
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DOI: https://doi.org/10.1007/3-540-61723-X_1018
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