A New Method for the Minimum Concave Cost Transportation Problem in Smart Transportation

2019 ◽  
pp. 363-369
Author(s):  
Chuan Li ◽  
Zhengtian Wu ◽  
Baochuan Fu ◽  
Chuangyin Dang ◽  
Jinjin Zheng
Keyword(s):  
Transportation Problem ◽  
New Method ◽  
Smart Transportation ◽  
Concave Cost

Perishing Goods Transportation Problem

2019 ◽  
pp. 315-338
Author(s):  
Ocotlán Díaz-Parra ◽  
Jorge A. Ruiz-Vanoye ◽  
Alejandro Fuentes-Penna ◽  
Ricardo A. Barrera-Cámara ◽  
Miguel A. Ruiz-Jaimes ◽  
...  
Keyword(s):  
Transportation Problem ◽  
Mathematical Optimization ◽  
Economic Losses ◽  
Perishable Products ◽  
Extreme Conditions ◽  
Smart Transportation ◽  
Transportation Modes ◽  
Mathematical Optimization Model ◽  
Transportation Times ◽  
Fresh Products

The smart transportation of farming must carry food from agriculture, livestock, and fisheries from one location to another using diverse types of transportation modes to improve the wellbeing of citizens. The mathematical optimization model proposed in this chapter represents the problem of transportation of perishable products which aims to minimize costs and optimize transportation times and costs. Reduction of the time of transportation of perishable products increases the likelihood of delivering fresh products and minimizes economic losses. Transportation time and temperature suitable for the conservation of the product are priorities in this type of problem because the product is transported in time reduces the probability that the product will be exposed to extreme conditions that favor its decomposition. To check the feasibility of the model, this study proposes a set of instances subject to an application obtained a series of solutions that are analyzed to identify if there is a feasible solution.

Trapezoidal fuzzy model to optimize transportation problem

2016 ◽  
Vol 07 (03) ◽  
pp. 1650028 ◽  
Author(s):  
Nirbhay Mathur ◽  
Pankaj Kumar Srivastava ◽  
Ajit Paul
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Fuzzy Model ◽  
Optimal Solution ◽  
Transportation Cost ◽  
New Method ◽  
Trapezoidal Fuzzy Numbers ◽  
North West ◽  
Fuzzy Environment ◽  
Practical Usefulness

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.

scholarly journals PSK Method for Solving Type-1 and Type-3 Fuzzy Transportation Problems

Fuzzy Systems ◽  
2017 ◽  
pp. 367-392 ◽  
Author(s):  
P. Senthil Kumar
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Solution Procedure ◽  
New Method ◽  
Ranking Procedure ◽  
Multiplication Operation ◽  
Fuzzy Transportation Problem ◽  
Type 3

In conventional transportation problem (TP), supplies, demands and costs are always certain. In this paper, the author tried to categories the TP under the mixture of certain and uncertain environment and formulates the problem and utilizes the crisp numbers, triangular fuzzy numbers (TFNs) and trapezoidal fuzzy numbers (TrFNs) to solve the TP. The existing ranking procedure of Liou and Wang is used to transform the type-1 and type-3 fuzzy transportation problem (FTP) into a crisp one so that the conventional method may be applied to solve the TP. The solution procedure differs from TP to type-1 and type-3 FTP in allocation step only. Therefore, the new method called PSK method and new multiplication operation on TrFN is proposed to find the mixed optimal solution in terms of crisp numbers, TFNs and TrFNs. The main advantage of this method is computationally very simple, easy to understand and also the optimum objective value obtained by our method is physically meaningful. The effectiveness of the proposed method is illustrated by means of a numerical example.

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