Fuzzy goal programming- an additive model
Fuzzy Sets and Systems
Multiple objective linear fractional programming: a fuzzy set theoretic approach
Fuzzy Sets and Systems
Fuzzy approaches for multiple criteria linear fractional optimization: a comment
Fuzzy Sets and Systems
Pareto optimality for multiobjective linear fractional programming problems with fuzzy parameters
Information Sciences: an International Journal
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy mathematical programming for multi objective linear fractional programming problem
Fuzzy Sets and Systems - Theme: Decision and optimization
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
Mathematical and Computer Modelling: An International Journal
Information Sciences: an International Journal
Perturbation analysis of fuzzy linear systems
Information Sciences: an International Journal
Interactive multiobjective fuzzy random programming through the level set-based probability model
Information Sciences: an International Journal
Fuzzy goal programming approach to multiobjective linear plus linear fractional programming problem
AMERICAN-MATH'11/CEA'11 Proceedings of the 2011 American conference on applied mathematics and the 5th WSEAS international conference on Computer engineering and applications
International Journal of Bio-Inspired Computation
Robust shortest path problem based on a confidence interval in fuzzy bicriteria decision making
Information Sciences: an International Journal
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This paper presents the use of a Taylor series for fuzzy multiobjective linear fractional programming problems (FMOLFP). The Taylor series is a series expansion that a representation of a function. In the proposed approach, membership functions associated with each objective of fuzzy multiobjective linear fractional programming problem transformed by using a Taylor series are unified. Thus, the problem is reduced to a single objective. Practical applications and numerical examples are used in order to show the efficiency and superiority of the proposed approach.