This paper considers a Biobjective transportation problem with various fuzzy objective functions coefficients. Fuzzy coefficients can be of different types such as triangular, trapezoidal, (semi) L 􀀀 R, or at (semi) L 􀀀 R fuzzy numbers. First, we convert the problem to a parametric interval Biobjective transportation problem using-cuts of fuzzy coefficients. Then, we consider a fix-cut and obtain a necessarily weak efficient solution to the yielded interval Biobjective program by a new algorithm. It uses basic feasible solutions and the parametric simplex algorithm. Furthermore, we suggest another algorithm for finding a reasonable solution, called -necessarily weak efficient, to the main Biobjective transportation problem. To illustrate the validity and performance of the proposed algorithms, we present some numerical examples.

We apply a primal-dual simplex algorithm for solving the Biobjective min imum cost-time network flow problem such that the total shipping cost and the total shipping fixed time are considered as the first and second objective functions, respectively. To convert the proposed model into a single-objective parametric one, the weighted sum scalarization technique is commonly used. This problem is a mixed-integer programming, which the decision variables are directly dependent together. Generally, the previous works have consid ered the linear Biobjective problem with the traditional network flow con straints, while in this paper, corresponding to each flow variable, a binary variable is defined. These zero-one variables are utilized to describe a fixed shipping time for positive flows. The proposed method is successful in finding all supported efficient solutions of a real numerical example.

transportation problem is a linear programming which considers minimum cost for shipping a product from some origins to other destinations such as from factories to warehouse, or from a warehouse to supermarkets. To solve this problem simplex algorithmis utilized. In real projects costs and the value of supply and demands are fuzzy numbers and it is expected that optimal solutions for determining the value of commodities transported from a source to a destination be obtained as a fuzzy. So the first idea is to present the in the full fuzzy condition and then an algorithmwhich is of importance for solving such a problem. In this article, a new algorithm is suggested for solving fully fuzzy transportation problem. This algorithm transforms the fully fuzzy transportation problem into a triple-objective problem and then it utilizes a weighted method for solving multi-objective problems and solves the new problem using simplex transportation method. At the end, the suggested method is utilized for the real data.

We present a modification of three existing methods for finding a basic feasible solution for capacitated transportation problem. To obtain an optimal solution, eht simplex algorithm for bounded variables is applied. Special properties of transportation problem help us to operate each step of simplex algorithm directly on the transportation tableau. At last, numerical examples are represented to illustrate our method.

In this paper, we study the linear fractional transportation problem with uncertain parameters. After recalling some de nitions, concepts and theorems in uncertainty theory we present three approaches for solving this problem. First we consider the expected value of the objective function together with the expectation of satisfying constraints. Optimizing the expected value of the objective function with considering chance constrained method for the restrictions is our second approach. In the third approach we add the objective function to the constraints and solve again the problem by chance constrained method. A numerical example is solved by three approaches and their solutions are compared.

In classical transport models, it is always assumed that parameters such as the distance from each supply node to each demand node or the cost of transferring goods from one node to another, as well as quantities such as supply and demand are definite and definite amounts. But in real matters, considering these assumptions is not logical. On the other hand, there may be a real problem in mathematical modeling with a variety of ambiguities in data simultaneously. In this paper, we consider a transport problem in which two types of fuzzy and grey data appear simultaneously. In the model under study, it is assumed that the coefficients of the grey objective function and the fuzzy supply and demand quantities are assumed. In this paper, we prove that by whitening grey numbers and defuzzification of the fuzzy numbers, the original problem can be turned into a crisp transport problem. Finally, with a numerical example, we describe the proposed method.

We consider Biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the Biobjective problems. The rst and second approaches are extensions of the labeling method to solve the single objective problem and the third approach is based on dynamic programming. The labeling methods usually producing several nondominated paths, we propose a fuzzy number ranking method to determine a fuzzy shortest path. Illustrative examples are worked out to show the e ectiveness of our algorithms.

The paper talks about the pentagonal Neutrosophic sets and its operational law. The paper presents the N N N, ,     cut of single valued pentagonal Neutrosophic numbers and additionally introduced the arithmetic operation of single-valued pentagonal Neutrosophic numbers. Here, we consider a transportation problem with pentagonal Neutrosophic numbers where the supply, demand and transportation cost is uncertain. Taking the benefits of the properties of ranking functions, our model can be changed into a relating deterministic form, which can be illuminated by any method. Our strategy is easy to assess the issue and can rank different sort of pentagonal Neutrosophic numbers. To legitimize the proposed technique, some numerical tests are given to show the adequacy of the new model.