A linguistic intelligent user guide for method selection in multi-objective decision support systems

Zhang, G; Lu, J

A linguistic intelligent user guide for method selection in multi-objective decision support systems

Zhang, G

Lu, J

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Publication Type:: Journal Article
Citation:: Information Sciences, 2009, 179 (14), pp. 2299 - 2308
Issue Date:: 2009-06-27

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Field	Value	Language
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2009-06-27	en_US
dc.identifier.citation	Information Sciences, 2009, 179 (14), pp. 2299 - 2308	en_US
dc.identifier.issn	0020-0255	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8921
dc.description.abstract	Some multi-objective decision-making (MODM) methods are more effective than others for particular decision problems and/or particular decision makers. It is therefore necessary to provide a set of MODM methods in a multi-objective decision support system (MODSS) to support a wide range of problem solving. However, it is always difficult for decision makers to select the most suitable method for individual cases because MODM methods involve a deep knowledge of mathematics. To handle this difficulty, this study develops a MODM method selection guide supported by a fuzzy matching optimization method. In this paper, we first present the modelling process for the knowledge of characteristics of the main MODM methods. We then present related matching techniques between the characteristics of a real-world decision-making situation and a set of predefined situation descriptions (characteristics of a MODM method) where the elements of the two sets may be expressed by linguistic terms. Based on this process, a fuzzy matching optimization-based MODM method selection approach is proposed. The approach applies general fuzzy numbers, fuzzy distance, fuzzy multi-criteria decision-making concepts, and rule-based inference techniques to recommend the most suitable method from a MODM method-base. The approach is adopted in a linguistic intelligent user guide within a MODSS. Experiments have shown that the development of the linguistic intelligent user guide can increase the ability of the MODSS to support decision makers in arriving at a satisfactory solution in a most effective way. © 2009 Elsevier Inc. All rights reserved.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0557154
dc.relation	http://purl.org/au-research/grants/arc/DP0559213
dc.relation.ispartof	Information Sciences	en_US
dc.relation.isbasedon	10.1016/j.ins.2009.01.043	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A linguistic intelligent user guide for method selection in multi-objective decision support systems	en_US
dc.type	Journal Article
utslib.citation.volume	14	en_US
utslib.citation.volume	179	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
dc.location.activity	ISI:000266646900002	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	14	en_US
pubs.publication-status	Published	en_US
pubs.volume	179	en_US

Abstract:

Some multi-objective decision-making (MODM) methods are more effective than others for particular decision problems and/or particular decision makers. It is therefore necessary to provide a set of MODM methods in a multi-objective decision support system (MODSS) to support a wide range of problem solving. However, it is always difficult for decision makers to select the most suitable method for individual cases because MODM methods involve a deep knowledge of mathematics. To handle this difficulty, this study develops a MODM method selection guide supported by a fuzzy matching optimization method. In this paper, we first present the modelling process for the knowledge of characteristics of the main MODM methods. We then present related matching techniques between the characteristics of a real-world decision-making situation and a set of predefined situation descriptions (characteristics of a MODM method) where the elements of the two sets may be expressed by linguistic terms. Based on this process, a fuzzy matching optimization-based MODM method selection approach is proposed. The approach applies general fuzzy numbers, fuzzy distance, fuzzy multi-criteria decision-making concepts, and rule-based inference techniques to recommend the most suitable method from a MODM method-base. The approach is adopted in a linguistic intelligent user guide within a MODSS. Experiments have shown that the development of the linguistic intelligent user guide can increase the ability of the MODSS to support decision makers in arriving at a satisfactory solution in a most effective way. © 2009 Elsevier Inc. All rights reserved.

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http://hdl.handle.net/10453/8921