|Title:||Solution approach to a special class of full fuzzy linear programming problems||Journal:||Procedia Computer Science||Volume:||162||First page:||260||Last page:||266||Conference:||7th International Conference on Information Technology and Quantitative Management, ITQM 2019; Granada; Spain; 3 November 2019 through 6 November 2019||Issue Date:||1-Jan-2019||Rank:||M33||ISSN:||1877-0509||DOI:||10.1016/j.procs.2019.11.283||Abstract:||
A wide variety of solution approaches to linear programming problems in fuzzy environment are proposed in the recent literature. For this study we consider a linear programming problem with fuzzy inequality constraints, and both coefficients and decision variables described by trapezoidal fuzzy numbers. Our solution approach takes into consideration decision maker's acceptance degree of the violated fuzzy constraints. We use the interval expectation of the trapezoidal fuzzy numbers to transform the original problem into an interval optimization problem. Then, using an order relation to rank the intervals; and handling the acceptance degree of the violated fuzzy constraints as a parameter in the optimization model, we analyze the Pareto optimal solutions to a parametric bi-objective linear programming problem. For a fixed value of the acceptance degree provided by the decision maker, but after a parametric analysis with respect to the parameter used for aggregating the two objectives, the decision maker becomes better informed about the nature of the problem he has to complete. We illustrate our new solution approach using numerical examples found in the literature, and emphasize its advantages.
|Keywords:||full fuzzy linear program | fuzzy inequality constraint | interval optimization | Pareto optimal solution | trapezoidal fuzzy number||Publisher:||Elsevier||Project:||Optimization of Distributive and Reverse Flows in Logistic Systems|
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