In this paper a fuzzy transportation problem under a fuzzy environment is solved using octagonal fuzzy numbers.The transportation problem is significant and has been widely studied in the field of applied mathematics ...In this paper a fuzzy transportation problem under a fuzzy environment is solved using octagonal fuzzy numbers.The transportation problem is significant and has been widely studied in the field of applied mathematics to solve a system of linear equations in many applications in science.Systems of concurrent linear equations play a vital major role in operational research.The main perspective of this research paper is to find out the minimum amount of transportation cost of some supplies through a capacitated network formerly the availability and the demand notes are octagonal fuzzy numbers.Octagonal fuzzy numbers are used and showed a membership function.To illustrate this method,a fuzzy transportation problem is solved by using octagonal fuzzy numbers using the ranking technique.It is shown that it is the best optimal solution and it is demonstrated with a numerical example.展开更多
The main aim of this paper is to develop an approach based on trapezoidal fuzzy numbers to optimize transportation problem in fuzzy environment.The present algorithm has representation of availability,demand and trans...The main aim of this paper is to develop an approach based on trapezoidal fuzzy numbers to optimize transportation problem in fuzzy environment.The present algorithm has representation of availability,demand and transportation cost as trapezoidal fuzzy numbers.This algorithm is found quicker in terms of runtime as comparison to fuzzy VAM discussed in[Kaur A.,Kumar A.,A new method for solving fuzzy transportation problem using ranking function,Appl.Math.Model.35:5652–5661,2011;Ismail Mohideen S.,Senthil Kumar P.,A comparative study on transportation problem in fuzzy environment,Int.J.Math.Res.2:151–158,2010].On the other hand this technique gives much better results than some classical methods like north-west corner and least cost method.Another benefit of this algorithm is that for certain transportation problems it directly gives optimal solution.It is one of the simplest methods to apply and perceive.Practical usefulness of the new method over other existing methods is demonstrated with two numerical examples.展开更多
文摘In this paper a fuzzy transportation problem under a fuzzy environment is solved using octagonal fuzzy numbers.The transportation problem is significant and has been widely studied in the field of applied mathematics to solve a system of linear equations in many applications in science.Systems of concurrent linear equations play a vital major role in operational research.The main perspective of this research paper is to find out the minimum amount of transportation cost of some supplies through a capacitated network formerly the availability and the demand notes are octagonal fuzzy numbers.Octagonal fuzzy numbers are used and showed a membership function.To illustrate this method,a fuzzy transportation problem is solved by using octagonal fuzzy numbers using the ranking technique.It is shown that it is the best optimal solution and it is demonstrated with a numerical example.
文摘The main aim of this paper is to develop an approach based on trapezoidal fuzzy numbers to optimize transportation problem in fuzzy environment.The present algorithm has representation of availability,demand and transportation cost as trapezoidal fuzzy numbers.This algorithm is found quicker in terms of runtime as comparison to fuzzy VAM discussed in[Kaur A.,Kumar A.,A new method for solving fuzzy transportation problem using ranking function,Appl.Math.Model.35:5652–5661,2011;Ismail Mohideen S.,Senthil Kumar P.,A comparative study on transportation problem in fuzzy environment,Int.J.Math.Res.2:151–158,2010].On the other hand this technique gives much better results than some classical methods like north-west corner and least cost method.Another benefit of this algorithm is that for certain transportation problems it directly gives optimal solution.It is one of the simplest methods to apply and perceive.Practical usefulness of the new method over other existing methods is demonstrated with two numerical examples.
