A fuzzy goal approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters

Wu, F; Zhang, G; Lu, J

A fuzzy goal approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters

Wu, F Zhang, G

Lu, J

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Publication Type:: Conference Proceeding
Citation:: Applied Computational Intelligence - Proceedings of the 6th International FLINS Conference, 2004, pp. 304 - 307
Issue Date:: 2004-12-01

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Field	Value	Language
dc.contributor.author	Wu, F	en_US
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	2004-12-01	en_US
dc.identifier.citation	Applied Computational Intelligence - Proceedings of the 6th International FLINS Conference, 2004, pp. 304 - 307	en_US
dc.identifier.isbn	9812388737	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1827
dc.description.abstract	Many business decisions can be modeled as multiple objective linear programming (MOLP) problems. When formulating a MOLP problem, objective functions and constraints involve many parameters which possible values are assigned by the experts who are often imprecisely or ambiguously known. So, it would be more appropriate for these parameters to be represented by fuzzy numbers. In this paper, a new fuzzy goal approximate algorithm is developed for solving fuzzy multiple objective linear programming (FMOLP) problems with fuzzy parameters when the fuzzy goals for the objective functions need to be achieved. And an illuminative example is also given to illustrate the algorithm developed.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0211701
dc.relation.ispartof	Applied Computational Intelligence - Proceedings of the 6th International FLINS Conference	en_US
dc.title	A fuzzy goal approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080105 Expert Systems	en_US
dc.location.activity	Blankenberghe, Belgium	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.publication-status	Published	en_US

Abstract:

Many business decisions can be modeled as multiple objective linear programming (MOLP) problems. When formulating a MOLP problem, objective functions and constraints involve many parameters which possible values are assigned by the experts who are often imprecisely or ambiguously known. So, it would be more appropriate for these parameters to be represented by fuzzy numbers. In this paper, a new fuzzy goal approximate algorithm is developed for solving fuzzy multiple objective linear programming (FMOLP) problems with fuzzy parameters when the fuzzy goals for the objective functions need to be achieved. And an illuminative example is also given to illustrate the algorithm developed.

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http://hdl.handle.net/10453/1827