An experimental study of newly proposed initial basic feasible solution methods for a transportation problem

OPSEARCH ◽  
2021 ◽  
Author(s):  
M. Mathirajan ◽  
Sujan Reddy ◽  
M. Vimala Rani
Keyword(s):  
Experimental Study ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Basic Feasible Solution ◽  
Solution Methods

scholarly journals Statistical Methods for Solving Transportation Problems

2019 ◽  
Vol 25 (2) ◽  
pp. 10-13
Author(s):  
Alina Baboş
Keyword(s):  
Linear Programming ◽  
Statistical Methods ◽  
Approximation Method ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Basic Feasible Solution ◽  
Statistical Tools ◽  
Numerical Examples ◽  
North West ◽  
Shipping Cost

Abstract Transportation problem is one of the models of Linear Programming problem. It deals with the situation in which a commodity from several sources is shipped to different destinations with the main objective to minimize the total shipping cost. There are three well-known methods namely, North West Corner Method Least Cost Method, Vogel’s Approximation Method to find the initial basic feasible solution of a transportation problem. In this paper, we present some statistical methods for finding the initial basic feasible solution. We use three statistical tools: arithmetic and harmonic mean and median. We present numerical examples, and we compare these results with other classical methods.

scholarly journals A NEW APPROACH TO FIND THE INITIAL BASIC FEASIBLE SOLUTION OF A TRANSPORTATION PROBLEM

2018 ◽  
Vol 6 (5) ◽  
pp. 321-325 ◽  
Author(s):  
Ravi Kumar R ◽  
Radha Gupta ◽  
Karthiyayini O
Keyword(s):  
Transportation Problem ◽  
Feasible Solution ◽  
Cost Minimization ◽  
Optimization Technique ◽  
Transportation Cost ◽  
Basic Feasible Solution ◽  
Standard Methods ◽  
North West ◽  
A New Technique ◽  
Optimum Solution

Transportation problem (TP) in operations research is a widely used optimization technique to study the problems concerned with transporting goods from production places to sale points. The TP may have one or more objectives such as minimization of transportation cost, minimization of distance with respect to time, and so on. There is a systematic method to solve such problems. For this, we find the Initial Basic Feasible Solution (IBFS) to the given problem. North West corner method, least cost method, Vogel’s approximation method are the standard methods one uses to find the IBFS.  In recent years, there are several other methods are proposed to solve such problems. In this paper, we propose a new technique named as Direct Sum Method (DSM) and its effectiveness is compared with the standard methods. The result shows that it is easy to compute and near to the optimum solution of the problem.

Solving interval-valued transportation problem using a new ranking function for octagonal fuzzy numbers

2022 ◽  
Author(s):  
Monika Bisht ◽  
Rajesh Dangwal
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Feasible Solution ◽  
Interval Data ◽  
Ranking Function ◽  
Basic Feasible Solution ◽  
Numerical Example ◽  
Fuzzy Transportation Problem ◽  
Ranking Technique ◽  
Interval Valued

In this paper, we introduce a new method to solve Interval-Valued Transportation Problem (IVTP) to deal with those problems of transportation wherein the information available is imprecise. First, a newly proposed fuzzification method is used to convert the IVTP to octagonal fuzzy transportation problem and then with the help of ranking function proposed in this paper, the fuzzy transportation problem is converted into crisp transportation problem. Lastly, Initial Basic Feasible Solution (IBFS) of this problem is obtained using Vogel’s Approximation Method and the solution is improved using Modified Distribution (MODI) method. A numerical example with interval data is solved using the proposed algorithm to make comparison of the solution with some other methods. Also, a numerical example with parameters in the form of octagonal fuzzy numbers is illustrated to compare the effectiveness of the proposed ranking technique. The proposed fuzzification and ranking technique can be used in the other fields of decision making dealing with the data in the same form as considered in this paper.

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