輸送モデルの非線形輸送費最適解とファジイモデル

Transportation costs are central issue for the resource allocation problems, which deal with principally cost minimization of transportation from supply to demand areas. Many researchers used linear programming methods to study minimization of transportation cost, because linear models also help to analyze and develop planning methods. Lately, fuzzy linear programming methods have been studied and introduced as a complementary. procedure. However, with this method, each unit cost along the transportation cost surface is regularly fixed. Generally, each transport cost unit is a function of traffic condition and distance under study, Based on these facts, this paper examines the practical issues of one aspect of the transportation problem in relation to the nonlinear cost function associated with traffic condition and distance. First, this paper shows that an optimal solution to a linear programming of transportation problem applies the Lagrange multiplier method. The results indicate that the fuzzy optimal solution ( for a case that introduces the Lagrange optimal solution to the fuzzy linear programming ) is a nonlinear transportation cost function. Second, a fuzzy optimal solution using an ordinary simplex method was applied. The results confirmed that the convergence iterating value for the MODI method finally astringed. This indicates that the fuzzy solution model can be applied for an optimal solution using the repetition of the MODI method.