Fuzzy goal programming algorithm for solving decentralized bi-level multi-objective programming problems

This paper presents fuzzy goal programming (FGP) algorithm for solving decentralized bi-level multi-objective programming (DBL-MOP) problems with a single decision maker at the upper level and multiple decision makers at the lower level. A FGP algorithm for DBL-multi-objective linear programming (DB...

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Bibliographic Details
Published in:Fuzzy sets and systems Vol. 160; no. 18; pp. 2701 - 2713
Main Author: Baky, Ibrahim A.
Format: Journal Article
Language:English
Published: Kidlington Elsevier B.V 16.09.2009
Elsevier
Subjects:
Applied sciences
Circuit properties
Computer science; control theory; systems
Control theory. Systems
Decentralized bi-level programming
Digital circuits
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
Exact sciences and technology
Fuzzy goal programming
Fuzzy mathematical programming
Goal programming
Information, signal and communications theory
Linear fractional programming
Mathematical methods
Miscellaneous
Multi-objective programming
System theory
Telecommunications and information theory
Theoretical computing
Fuzzy goal programming
Decentralized bi-level programming
Multi-objective programming
Fuzzy mathematical programming
Linear fractional programming
Goal programming
Fuzzy system
Linear programming
Fuzzy set
Algorithm
Engineering
Information processing
Mathematical programming
ISSN:0165-0114, 1872-6801
Online Access:Get full text
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Summary:This paper presents fuzzy goal programming (FGP) algorithm for solving decentralized bi-level multi-objective programming (DBL-MOP) problems with a single decision maker at the upper level and multiple decision makers at the lower level. A FGP algorithm for DBL-multi-objective linear programming (DBL-MOLP) problems is proposed. This algorithm is extended to solve bi-level multi-objective linear fractional programming (DBL-MOLFP) problems. In the proposed algorithm, the membership functions for the defined fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by ULDM are developed in the model formulation of the problem. Then FGP approach is used to achieve highest degree of each of the membership goals by minimizing their deviational variables and thereby obtaining the most satisfactory solution for all decision makers. Illustrative numerical examples are given to demonstrate the proposed algorithm.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2009.02.022