شماره ركورد كنفرانس :
4330
عنوان مقاله :
A Fuzzy Flexible Linear Programming Model Based on Feasibility and Efficiency Concept of Solutions
عنوان به زبان ديگر :
A Fuzzy Flexible Linear Programming Model Based on Feasibility and Efficiency Concept of Solutions
پديدآورندگان :
Nasseri .S.H nasseri@umz.ac.ir University of Mazandaran , Ramzannia-Keshteli .G.A gh.ramezan@stu.umz.ac.ir University of Mazandaran
كليدواژه :
Feasibility and efficiency of solution , Fuzzy flexible linear programming , Multi parametric programming , Sensitivity analysis
عنوان كنفرانس :
هفدهمين كنفررانس ملي سيستم هاي فازي، پانزدهمين كنفرانس ملي سيستم هاي هوشمند و ششمين كنگره ملي مشترك سيستم هاي فازي و هوشمند ايران
چكيده فارسي :
Recently, Fuzzy Flexible Linear Programming (FFLP) problem is introduced by
some researchers. In particular, a new concept of feasibility and efficiency for the solution of
these problems in introduced. As we know, in the most suggested approaches for solving FFLP
problems the optimal value of the flexible solution to be obtained in two phases. Moreover,
some deficiencies is appeared in the literature such as: 1) some of the suggested solving
processes need to achieve the optimal solutions by solving two parametric LP problems while
the proposed algorithm in this study can obtain the optimal solution by just solving one
equivalent problem. Hence, this is more comfortable for the decision makers due to it are
easier for the computational task. 2) In the sensitivity analysis process by their approach, we
must repeat the solving process of both problems for any changes in the parameters while in
the suggested approach, we able to achieve the optimal solution in the simple way.
چكيده لاتين :
Recently, Fuzzy Flexible Linear Programming (FFLP) problem is introduced by
some researchers. In particular, a new concept of feasibility and efficiency for the solution of
these problems in introduced. As we know, in the most suggested approaches for solving FFLP
problems the optimal value of the flexible solution to be obtained in two phases. Moreover,
some deficiencies is appeared in the literature such as: 1) some of the suggested solving
processes need to achieve the optimal solutions by solving two parametric LP problems while
the proposed algorithm in this study can obtain the optimal solution by just solving one
equivalent problem. Hence, this is more comfortable for the decision makers due to it are
easier for the computational task. 2) In the sensitivity analysis process by their approach, we
must repeat the solving process of both problems for any changes in the parameters while in
the suggested approach, we able to achieve the optimal solution in the simple way.