Solving fuzzy multi-objective linear programming problems using deviation degree measures and weighted max-min method
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Date
2013-06-01
Open Access Location
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
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Elsevier
Under an Elsevier user license
Under an Elsevier user license
Abstract
This paper proposes a method for solving fuzzy multi-objective linear programming (FMOLP) problems where all the coefficients are triangular fuzzy numbers and all the constraints are fuzzy equality or inequality. Using the deviation degree measures and weighted max–min method, the FMOLP problem is transformed into crisp linear programming (CLP) problem. If decision makers fix the values of deviation degrees of two side fuzzy numbers in each constraint, then the δ-pareto-optimal solution of the FMOLP problems can be obtained by solving the CLP problem. The bigger the values of the deviation degrees are, the better the objectives function values will be. So we also propose an algorithm to find a balance-pareto-optimal solution between two goals in conflict: to improve the objectives function values and to decrease the values of the deviation degrees. Finally, to illustrate our method, we solve a numerical example.
Description
Keywords
Fuzzy multi-objective linear programming, Fuzzy constraints, Triangular fuzzy numbers, Deviation degree, Weighted max–min method
Citation
Applied Mathematical Modelling, 2013, 37 (10-11), pp. 6855 - 6869