The Transportation Problem with Objective of Simultaneous Minimization of Total Transportation Cost and Transportation Time to Each Destination

OPSEARCH ◽  
1998 ◽  
Vol 35 (3) ◽  
pp. 238-260
Author(s):  
G. V. Sarma
Keyword(s):  
Transportation Problem ◽  
Transportation Cost ◽  
Transportation Time ◽  
Total Transportation Cost

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.

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 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. 

Fuzzy Transportation Problem by Using Triangular, Pentagonal and Heptagonal Fuzzy Numbers With Lagrange's Polynomial to Approximate Fuzzy Cost for Nonagon and Hendecagon

2020 ◽  
Vol 9 (1) ◽  
pp. 112-129
Author(s):  
Ashok Sahebrao Mhaske ◽  
Kirankumar Laxmanrao Bondar
Keyword(s):  
Transportation Problem ◽  
Operational Research ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Transportation Cost ◽  
Fuzzy Transportation Problem ◽  
Total Transportation Cost ◽  
Fuzzy Cost

The transportation problem is a main branch of operational research and its main objective is to transport a single uniform good which are initially stored at several origins to different destinations in such a way that the total transportation cost is minimum. In real life applications, available supply and forecast demand, are often fuzzy because some information is incomplete or unavailable. In this article, the authors have converted the crisp transportation problem into the fuzzy transportation problem by using various types of fuzzy numbers such as triangular, pentagonal, and heptagonal fuzzy numbers. This article compares the minimum fuzzy transportation cost obtained from the different method and in the last section, the authors introduce the Lagrange's polynomial to determine the approximate fuzzy transportation cost for the nanogon (n = 9) and hendecagon (n = 11) fuzzy numbers.

Solving the fully fuzzy multi-objective transportation problem based on the common set of weights in DEA

2020 ◽  
Vol 39 (3) ◽  
pp. 3099-3124
Author(s):  
M. Bagheri ◽  
A. Ebrahimnejad ◽  
S. Razavyan ◽  
F. Hosseinzadeh Lotfi ◽  
N. Malekmohammadi
Keyword(s):  
Relative Efficiency ◽  
Transportation Problem ◽  
Real Life ◽  
Transportation Cost ◽  
Multi Objective ◽  
Decision Making Unit ◽  
Common Set Of Weights ◽  
The Common ◽  
Total Transportation Cost ◽  
Fuzzy Dea

A transportation problem basically deals with the problem which aims to minimize the total transportation cost or maximize the total transportation profit of distributing a product from a number of sources or origins to a number of destinations. While, in general, most of the real life applications are modeled as a transportation problem (TP) with the multiple, conflicting and incommensurate objective functions. On the other hand, for some reason such as shortage of information, insufficient data or lack of evidence, the data of the mentioned problem are not always exact but can be fuzzy. This type of problem is called fuzzy multi-objective transportation problem (FMOTP). There are a few approaches to solve the FMOTPs. In this paper, a new fuzzy DEA based approach is developed to solve the Fully Fuzzy MOTPs (FFMOTPs) in which, in addition to parameters of the MOTPs, all of the variables are considered fuzzy. This approach considers each arc in a FFMOTP as a decision making unit which produces multiple fuzzy outputs using the multiple fuzzy inputs. Then, by using the concept of the common set of weights (CSW) in DEA, a unique fuzzy relative efficiency is defined for each arc. In the following, the unique fuzzy relative efficiency is considered as the only attribute for the arcs. In this way, a single objective fully fuzzy TP (FFTP) is obtained that can be solved using the existing standard algorithms for solving this kind of TPs. A numerical example is provided to illustrate the developed approach.

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%

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 A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

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