A New Method to Solve Interval Transportation Problems (original) (raw)

Trisectional fuzzy trapezoidal approach to optimize interval data based transportation problem

Journal of King Saud University - Science, 2018

This research article puts forward a combination of two new thoughts to solve interval data based transportation problems (IBTPs). Firstly IBTP is converted to fuzzy transportation problem using trisectional approach and secondly a newly proposed ranking technique based on in-centre concept is applied for conversion to crisp number. It is supported with numerical illustrations to test the relevance of the scheme. Comparison with other existing methods confirms its significance for transportation problems having interval data.

Multiobjective transportation problem with interval cost, source and destination parameters

European Journal of Operational Research, 1999

In this paper, we focus on the solution procedure of the multiobjective transportation problem (MOTP) where the cost coecients of the objective functions, and the source and destination parameters have been expressed as interval values by the decision maker. This problem has been transformed into a classical MOTP where to minimize the interval objective function, the order relations that represent the decision maker's preference between interval pro®ts have been de®ned by the right limit, left limit, centre, and half-width of an interval. The constraints with interval source and destination parameters have been converted into deterministic ones. Finally, the equivalent transformed problem has been solved by fuzzy programming technique. Numerical examples have been provided to illustrate the solution procedure for three possible cases of the original problem.

Comparative Study of Optimum Solution Between Interval Transportation and Interval Transhipment Problem

International Journal of Advanced Science and Engineering, 2018

In this paper, a comparison of optimum solution between transportation and transhipment problem where the cost coefficients are the objective functions, and the source and destination parameters is expressed as interval values. The objective is to minimize the total transportation cost and the solution is obtained by converting the interval transportation problem into an equivalent interval transhipment problem. In some circumstances, interval transhipment will be less expensive than interval transportation , explained by means of numerical example.

A Solution Algorithm for Interval Transportation Problems via Time-Cost Tradeoff

JOURNAL OF ADVANCES IN MATHEMATICS

In this paper, an algorithm for solving interval time-cost tradeoff transportation problemsis presented. In this problem, all the demands are defined as intervalto determine more realistic duration and cost. Mathematical methods can be used to convert the time-cost tradeoff problems to linear programming, integer programming, dynamic programming, goal programming or multi-objective linear programming problems for determining the optimum duration and cost. Using this approach, the algorithm is developed converting interval time-cost tradeoff transportation problem to the linear programming problem by taking into consideration of decision maker (DM).

A New Approach for Finding an Optimal Solution for Integer Interval Transportation Problems

2010

In this paper a difierent approach namely separation method based on zero su‐x method is applied for flnding an optimal solution for integer transportation problems where transportation cost, supply and demand are intervals. The proposed method is a non fuzzy method. The solution procedure is illustrated with a numerical example. The separation method can be served as an important tool for the decision makers when they are handling various types of logistic problems having interval parameters.

New approach for solving intuitionistic fuzzy multi-objective transportation problem

Sādhanā, 2018

Multi-objective transportation problem (MOTP) under intuitionistic fuzzy (IF) environment is analysed in this paper. Due to the fluctuation of market scenario, we assume that the transportation cost, the supply and the demand parameters are not always precise. Hence, the parameters are imprecise, i.e., they are IF numbers. Considering the specific cut interval, the IF transportation cost matrix is converted to interval cost matrix in our proposed problem. Again, using the same concept, the IF supply and the IF demand of the MOTP are reduced to the interval form. Then the proposed MOTP is changed into the deterministic MOTP, which includes interval form of the objective functions. Two approaches, namely intuitionistic fuzzy programming and goal programming, are used to derive the optimal solutions of our proposed problem, and then the optimal solutions are compared. A numerical example is included to illustrate the feasibility and the applicability of the proposed problem. Finally, we present the conclusions with the future scopes of our study.

Dichotomized Incenter Fuzzy Triangular Ranking Approach to Optimize Interval Data Based Transportation Problem

Cybernetics and Information Technologies, 2018

This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated with these types of problems motivates authors to tackle it by converting interval to fuzzy numbers. This confront of conversion has been achieved by proposing a dichotomic fuzzification approach followed by a unique triangular incenter ranking approach to optimize interval data based transportation problems. A comparison with existing methods is made with the help of numerical illustrations. The algorithm proposed is found prompt in terms of the number of iteration involved and problem formation. This method is practical to handle the transportation problems not having a single valued data, but data in form of a range.

A new approach for solving intuitionistic fuzzy transportation problem of type-2

Annals of Operations Research, 2014

Multi-objective transportation problem (MOTP) under intuitionistic fuzzy (IF) environment is analysed in this paper. Due to the fluctuation of market scenario, we assume that the transportation cost, the supply and the demand parameters are not always precise. Hence, the parameters are imprecise, i.e., they are IF numbers. Considering the specific cut interval, the IF transportation cost matrix is converted to interval cost matrix in our proposed problem. Again, using the same concept, the IF supply and the IF demand of the MOTP are reduced to the interval form. Then the proposed MOTP is changed into the deterministic MOTP, which includes interval form of the objective functions. Two approaches, namely intuitionistic fuzzy programming and goal programming, are used to derive the optimal solutions of our proposed problem, and then the optimal solutions are compared. A numerical example is included to illustrate the feasibility and the applicability of the proposed problem. Finally, we present the conclusions with the future scopes of our study.

A Method For Solving A Bi-Objective Transportation Problem Under Fuzzy Environment

2017

A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.