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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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