Abstract
The present paper attempts to obtain the optimal solution for the fuzzy transportation problem with mixed constraints. In this paper, authors have proposed a new innovative approach for obtaining the optimal solution of mixed constraint fuzzy transportation problem. The method is illustrated using a numerical example and the logical steps are highlighted using a simple flowchart. As maximum transportation problems in real life have mixed constraints and these problems cannot be truly solved using general methods, so the proposed method can be applied for solving such mixed constraint fuzzy transportation problems to obtain the best optimal solutions.
Highlights
The most successful and noteworthy contribution of quantity analysis for solving business problems erstwhile in the physical distribution of products and services, is commonly referred to as transportation problems
In real life applications, the situation and conditions are different since various parameters of the transportation problems may or may not be known precisely due to various existing uncontrollable factors
A literature review about mixed constraint Fuzzy transportation problem (FTP) revealed no efficient method for finding its optimal solution
Summary
The most successful and noteworthy contribution of quantity analysis for solving business problems erstwhile in the physical distribution of products and services, is commonly referred to as transportation problems. In 2006, Adalkha et al [12] provided a heuristic algorithm for solving transportation problems with mixed constraints and extend the algorithm to find a more-for-less (MFL) solution, if one exists. Pandian and Natrajan [8] have developed fourier method for solving transportation problems with mixed constraints in 2010. Pandian and Anuradha [18] have introduced path method for finding a MFL optimal solution to Transportation problem in 2013. Pandian et al [15,16,17] studied new method to solve transportation problem with mixed constraints in 2014. In the present paper authors have attempted to find the optimal solution for fuzzy transportation problem with mixed constraints using Improved VAM method. Section-6, presents the significance and conclusion of the present study
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