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A genetic algorithm for combinational optimization problems with uncertainties

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Title: A genetic algorithm for combinational optimization problems with uncertainties
Authors: Hoshino, Kenta Browse this author
Igarashi, Hajime Browse this author →KAKEN DB
Issue Date: 8-Sep-2010
Publisher: IEEE
Journal Title: 2010 IEEE International Symposium on Computer-Aided Control System Design (CACSD)
Start Page: 368
End Page: 373
Publisher DOI: 10.1109/CACSD.2010.5612689
Abstract: This paper describes a genetic algorithm (GA) applied to combinational optimization problems in which the objective functions include uncertain constant parameters. In the present method, noises whose probabilistic distribution is assumed based on the problem environments are added to the parameters during the evaluations process. It is assumed that this allows us to make approximate evaluation of the expected values of the objective function under uncertainties. It is shown that the present method results in the robust solutions, which have higher expectation values than the ones obtained by the conventional GA, to the traveling salesman and knapsack problems with uncertainties.
Conference Name: 2010 IEEE International Symposium on Computer-Aided Control System Design (CACSD)
Conference Place: Yokohama
Rights: © 2010 IEEE. Reprinted, with permission, from Hoshino, K., Igarashi, H., A genetic algorithm for combinational optimization problems with uncertainties , 2010 IEEE International Symposium on Computer-Aided Control System Design (CACSD), Sep. 2010. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Hokkaido University products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Type: proceedings (author version)
URI: http://hdl.handle.net/2115/46847
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 五十嵐 一

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