scholarly journals OPTIMALISASI BIAYA PENDISTRIBUSIAN PRODUK DENGAN METODE TRANSPORTASI

2017 ◽  
Author(s):  
Tri Tri Hernawati
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Optimal Distribution ◽  
Process Step ◽  
Target Company ◽  
Initial Feasible Solution ◽  
Total Transportation Cost ◽  
The Right ◽  
Programming Step

Optimal distribution product is one of important aspect in reaching target company. The fault in distribution product can cause unmaximal profit. To avoid the fault in distribution product, we need to use the right method. Transportation Method is one of method wich is useful enough to optimized the distribution product. The transportation Problem is special type of Linear Programming problem wich deals with the distribution of single product (ow or finished) from various resources to various destination of demand. In such way that the total transportation cost is minimized. The solution of transportation problem is two step process. Step 1, to find Initial Feasible Solution (IFS) Programming. Step 2, From the IFS, to find the optimal solution. The IFS may or may not be optimal. If the IFS is not optimal, then it can be improved to give a better result. This process of Testing & Improving the IFS is called Modified Distribution Method.The aim of this research is to get the optimal distribution product for minimalizing total transportation cost. The result of the research shows minimalizing total transportation cost about 5,99%

scholarly journals An Empirical Study on Multi-objective Transportation Problem in Fuzzy Environment

2018 ◽  
Vol 7 (4.38) ◽  
pp. 748
Author(s):  
Manoranjan Mishra ◽  
Debdulal Panda
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Fuzzy Rule ◽  
Transportation Cost ◽  
Transportation System ◽  
Vital Role ◽  
Multi Objective ◽  
Transportation Models ◽  
Total Transportation Cost ◽  
Single Objective

For both in economical and social development of country transportation system plays a vital role. As it is directly involved with financial growth of the country, for that a complete well planned transportation infrastructure is necessary. Most of the transportation models are formulated with minimization of transportation cost as the basic objective. But consideration of transportation system with a single objective is not able to meet the various requirements of transportation industry for which it may not lead to the practical optimal solution. It bounds the decision makers (DMs) to consider several objectives at a time instead of single objective. To handle a multi-objective transportation problem with fixed parameters is a challenging issue; rather it is easy to consider all parameters in terms of linguistic variables. In this paper, a multi criteria multi-objective transportation models is formulated based on fuzzy relations under the fuzzy logic with several objectives like (i) minimization of total transportation cost and (ii) minimization of total transportation time. Another objective, maximization of the transported amount from a source to a destination is determined on the basis of previous two objectives. All the objectives are associated with multiple numbers of criteria like breakable items, shipping distance, service charge, mode of transportation etc. These relations are imprecise in nature and represented in terms of verbal words such as low, medium, high and very high. The fuzzy rule based multi-objective transportation problem is formulated and result is discussed. 

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Optimization of total transportation cost

2020 ◽  
Vol 26 (1) ◽  
pp. 57-63
Author(s):  
Adamu Isah Kamba ◽  
Suleiman Mansur Kardi ◽  
Yunusa Kabir Gorin Dikko
Keyword(s):  
Transportation Problem ◽  
Research Work ◽  
Minimum Cost ◽  
Transportation Cost ◽  
Strategic Decision ◽  
Distribution Method ◽  
North West ◽  
Total Transportation Cost ◽  
Transportation Schedule ◽  
Furniture Factory

In this research work, the study used transportation problem techniques to determine minimum cost of transportation of Gimbiya Furniture Factory using online software, Modified Distribution Method (MODI). The observation made was that if Gimbiya furniture factory, Birnin Kebbi could apply this model to their transportation schedule, it will help to minimize transportation cost at the factory to ₦1,125,000.00 as obtained from North west corner method, since it was the least among the two methods, North west corner method and Least corner method. This transportation model willbe useful for making strategic decision by the logistic managers of Gimbiya furniture factory, in making optimum allocation of the production from the company in Kebbi to various customers (key distributions) at a minimum transportation cost. Keywords: North West corner, Least corner, Transportation problem, minimum transportation.

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 Comparative Study of Ranking Methods for Fuzzy Transportation

2019 ◽  
pp. 1592-1602
Author(s):  
Sami Kadhem kareem Al thabhawi
Keyword(s):  
Linear Programming ◽  
Comparative Study ◽  
Programming Model ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Basic Solution ◽  
Ranking Methods ◽  
Fuzzy Variables ◽  
Accurate Comparison ◽  
Total Transportation Cost

There are several methods that are used to solve the traditional transportation problems whose units of supply, demand quantities, and cost transportation are known exactly. These methods obtain basic solution, and develop it to the best solution through a series of consecutive calculations to obtain the optimal solution.The steps are more complex with fuzzy variables, so this paper presents the disadvantages of solutions of the traditional ways with existence of variables in the fuzzy form.This paper also presents a comparison between the results that emerged after using different conversion ranking formulas to convert from fuzzy form to crisp form on the same numerical example with a full fuzzy form. The problem has been then converted into a linear programming model, and the BIG-M method to be later used to find the optimal solution that represents the number of units transferred from processing or supply centers to a number of demand centers based on the known cost of transportation.Achieving the goal of the problem is by finding the lowest total transportation cost,while the comparison is based on that value. The results are presented in acomprehensive table that organizes data and results in a way that facilitates quickand accurate comparison. An amendment to one of the order formats was suggested,because it has different results compared to other formulas. One of the rankingequations is modified, because it has different results compared to other methods..

scholarly journals PENYELESAIAN MODEL TRANSPORTASI MENGGUNAKAN METODE ASM

2020 ◽  
Vol 14 (1) ◽  
pp. 40
Author(s):  
Nurul Iftitah ◽  
Pardi Affandi ◽  
Akhmad Yusuf
Keyword(s):  
Transportation Problem ◽  
Feasible Solution ◽  
Direct Method ◽  
Optimal Solution ◽  
Transportation Model ◽  
Initial Feasible Solution ◽  
The Cost

(demand). the method that could be used for solving the transportation problem is to directly find the optimal solution. The direct method that used in this study id the ASM method for solving the balance transportation problem and revised ASM method for solving the unbalance transportation problem. This study aims to construct a transportation model using those methods and it solution. The method on this study is to identify the transportation model, construct the transportation model matrixes, construct an algorithm table using ASM method and to determine the optimal solution of the transportation problem. The obtained result from this study was the model ASM method could determine the optimum value without using initial feasible solution. On solving the unbalance transportation problem, there is an addition of dummy cell or column step. Then reducing the cost of cell and column and change the dummy cost with the biggest cost of reduced cell or column.

scholarly journals Application of fuzzy programming techniques to solve solid transportation problem with additional constraints

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Sharmistha Halder (Jana) ◽  
Biswapati Jana
Keyword(s):  
Transportation Problem ◽  
Real Life ◽  
Transportation Cost ◽  
Fuzzy Programming ◽  
Solid Transportation Problem ◽  
Generalized Gradient ◽  
Proposed Model ◽  
Programming Techniques ◽  
Total Transportation Cost ◽  
Additional Constraints

An innovative, real-life solid transportation problem is explained in a non-linear form. As in real life, the total transportation cost depends on the procurement process or type of the items and the distance of transportation. Besides, an impurity constraint is considered here. The proposed model is formed with fuzzy imprecise nature. Such an interesting model is optimised through two different fuzzy programming techniques and fractional programming methods, using LINGO-14.0 tools followed by the generalized gradient method. Finally, the model is discussed concerning these two different methods.

scholarly journals Solving Fuzzy Transportation Problem Using ASM Method and Zero Suffix Method

2021 ◽  
Vol 1 (01) ◽  
pp. 28-35
Author(s):  
Aurora Nur Aini ◽  
Ali Shodiqin ◽  
Dewi Wulandari
Keyword(s):  
Linear Programming ◽  
Fuzzy Number ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Optimal Solution ◽  
Demand And Supply ◽  
Transportation Problems ◽  
Initial Feasible Solution ◽  
Fuzzy Transportation Problem ◽  
Special Case

The transportation problem is a special case for linear programming. Sometimes, the amount of demand and supply in transportation problems can change from time to time, and thus it is justified to classify the transportation problem as a fuzzy problem. This article seeks to solve the Fuzzy transportation problem by converting the fuzzy number into crisp number by ranking the fuzzy number. There are many applicable methods to solve linear transportation problems. This article discusses the method to solve transportation problems without requiring an initial feasible solution using the ASM method and the Zero Suffix method. The best solution for Fuzzy transportation problems with triangular sets using the ASM method was IDR 21,356,787.50, while the optimal solution using the Zero Suffix method was IDR 21,501,225.00. Received February 5, 2021Revised April 16, 2021Accepted April 22, 2021

scholarly journals An Optimal Transportation Schedule of Mobile Equipment

2012 ◽  
Vol 10 (5) ◽  
Author(s):  
S. Guillén-Burguete ◽  
H. Sánchez-Larios ◽  
J.G Vázquez-Vázquez
Keyword(s):  
Optimal Solution ◽  
Road Construction ◽  
Transportation Cost ◽  
Convex Polyhedra ◽  
Mixed Integer ◽  
Time Intervals ◽  
Mixed Integer Linear Program ◽  
Arrival Times ◽  
Indefinite Number ◽  
Total Transportation Cost

Motivated by a problem faced by road construction companies, we develop a new model to obtain an optimaltransportation schedule of mobile machines which have to travel to execute tasks. In this problem, each task ischaracterized by the location where it is to be executed, a work-content in terms of machine-time units, and one ormore time intervals within which it can be performed. The machines can be transported from one location to anotherat any time, thus the problem has an indefinite number of variables. However, this indefinite number of variables canbe reduced to a definite one because, as we prove, the problem has an optimal solution in which the arrivals ofmachines occur only at certain time instants. The objective is to minimize the total transportation cost such that all thetasks are executed within their time intervals. The constraints ensuring that the tasks are processed within theirprescribed time intervals are nonlinear; nevertheless, due to the sets of the possible arrival times of the machinesforming bounded convex polyhedra, our problem can be transformed into a mixed integer linear program by the samedevice used in the decomposition principle of Dantzig-Wolfe.

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