Computing efficient solutions to fuzzy multiple objective linear programming problems

In this paper, we improve the fuzzy compromise approach of Guu and Wu by automatically computing proper membership thresholds instead of choosing them. Indeed, in practice, choosing membership thresholds arbitrarily may result in an infeasible optimization problem. Although we can adjust minimum sat...

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Bibliographic Details
Published in:Fuzzy sets and systems Vol. 157; no. 10; pp. 1328 - 1332
Main Authors: Li, Xue-quan, Zhang, Bo, Li, Hui
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 16.05.2006
Elsevier
Subjects:
Applied sciences
Circuit properties
Computer science; control theory; systems
Control theory. Systems
Digital circuits
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
Exact sciences and technology
Fuzzy compromise approach
Fuzzy multiple objective linear programming
Information, signal and communications theory
Mathematical methods
Max–min operator approach
Miscellaneous
System theory
Telecommunications and information theory
Theoretical computing
Two-phase approach
Fuzzy compromise approach
Fuzzy multiple objective linear programming
Max–min operator approach
Two-phase approach
Engineering
Fuzzy system
Optimization method
Information processing
Max-min operator approach
Linear programming
Fuzzy set
ISSN:0165-0114, 1872-6801
Online Access:Get full text
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Summary:In this paper, we improve the fuzzy compromise approach of Guu and Wu by automatically computing proper membership thresholds instead of choosing them. Indeed, in practice, choosing membership thresholds arbitrarily may result in an infeasible optimization problem. Although we can adjust minimum satisfaction degree to get fuzzy efficient solution, it sometimes makes the process of interaction more complicated. In order to overcome this drawback, a theoretically and practically more efficient two-phase max–min fuzzy compromise approach is proposed in this paper. Moreover, the efficiency of the two-phase approach is verified by an example.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2005.12.003