
Summary: This paper deals with fully fuzzy linear programming (FFLP) problem in which all parameters and variables are characterized by \(L - R\) fuzzy numbers. By a proposed approach, the FFLP problem is converted into the triple objective functions, and hence a single objective using the weighting method. Through this approach the problem is not transformed into the crisp linear programming problem (LPP) that is enable for obtaining fuzzy optimal solution and the corresponding fuzzy optimal solution which is more realistic to the real world problems. Then a numerical example is taken to the utility and clarify the practically and the efficiency of the approach.
T57-57.97, Applied mathematics. Quantitative methods, fuzzy optimal solution, \(L - R\) fuzzy numbers, fuzzy optimal solution, Linear programming, L-R fuzzy numbers, Fuzzy and other nonstochastic uncertainty mathematical programming, fully fuzzy linear programming, software GAMS, weighting method
T57-57.97, Applied mathematics. Quantitative methods, fuzzy optimal solution, \(L - R\) fuzzy numbers, fuzzy optimal solution, Linear programming, L-R fuzzy numbers, Fuzzy and other nonstochastic uncertainty mathematical programming, fully fuzzy linear programming, software GAMS, weighting method
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
