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JAIST Repository >
Center for Strategic Development of Science and Technology　2003-2008 >
JAIST PRESS Publications >
IFSR 2005 >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10119/3936
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| Title: | Decision Engineering Methodology |
| Authors: | Kazimierz, Zaras
Christian, Fonteix
Laszlo, Kiss
Jules, Thibault |
| Keywords: | neural network
genetic algorithm
Pareto domain
Rough Set Method
multi-criteria analysis
preferences
robustness analysis |
| Issue Date: | Nov-2005 |
| Publisher: | JAIST Press |
| Abstract: | In industry, decision makers are often confronted with multiobjective decision problems that are not easy to resolve. In this paper we suggest a comprehensive methodology which allows us to determine an adequate model predicting the performance criteria, to discretize the Pareto domain defined in terms of input parameters and to classify of large number of possible solutions from the Pareto domain with decision rules which are based on decision maker preferences. These rules are then applied to determine the preferred zone of operation. The whole approach we call the decision engineering methodology. |
| Description: | The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2146, Kobe, Japan
Symposium 1, Session 7 : Technology Creation Based on Knowledge Science Modeling and Systems(1) |
| Language: | ENG |
| URI: | http://hdl.handle.net/10119/3936 |
| ISBN: | 4-903092-02-X |
| Appears in Collections: | IFSR 2005
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Files in This Item:
| File |
Description |
Size | Format |
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| 20007.pdf | | 39Kb | Adobe PDF | View/Open |
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