DocumentCode :
2751726
Title :
Tools and Techniques for Managing Many-Criteria Decision-Making
Author :
Fleming, Peter J.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Sheffield Univ.
fYear :
2007
fDate :
1-5 April 2007
Firstpage :
21
Lastpage :
21
Abstract :
Summary form only given. Design problems arising in business and industry can often be conveniently formulated as multi-criteria decision-making problems. However, these often comprise a relatively large number of criteria. Through our close association with designers in industry and business we have devised a range of machine learning tools and associated techniques to address the special requirements of many-criteria decision-making. These include visualisation and analysis tools to aid the identification of features such as "hot-spots" and non-competing criteria, preference articulation techniques to assist in interrogating the search region of interest and methods to address the special computational demands of these problems. With the aid of test problems and real design exercises, we will demonstrate these approaches and also discuss alternative methods
Keywords :
decision making; learning (artificial intelligence); analysis tools; business design problems; industry design problems; machine learning tools; multicriteria decision-making problems; visualisation tools; Automatic control; Computational intelligence; Computer industry; Decision making; Electrical equipment industry; Engineering management; Industrial control; Machine learning; Testing; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Multicriteria Decision Making, IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0702-8
Type :
conf
DOI :
10.1109/MCDM.2007.369411
Filename :
4222977
Link To Document :
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