scholarly journals Rough interval Max Plus Algebra for Transportation Problems

2020 ◽  
Vol 9 (4) ◽  
pp. 58-60
Keyword(s):  
Operations Research ◽  
Interval Data ◽  
Transportation Problems ◽  
Suitable Solution ◽  
Algebra Approach ◽  
Max Algebra ◽  
Rough Interval ◽  
Research Domain

The traffic problem is an important problem which has been broadly learnt in Operations Research domain. This paper presents a new Rough Interval Max Algebra Approach (RIMAA) for solving the traffic problem with Rough Interval data. The proposed approach is simple and able to give a suitable solution to this problem. Finally, a descriptive example is given to evaluate performance of the proposed approach.

scholarly journals Rough interval Max Plus Algebra for Transportation Problems

2020 ◽  
Vol 9 (4) ◽  
pp. 58-60
Keyword(s):  
Operations Research ◽  
Interval Data ◽  
Transportation Problems ◽  
Suitable Solution ◽  
Algebra Approach ◽  
Max Algebra ◽  
Rough Interval ◽  
Research Domain

The traffic problem is an important problem which has been broadly learnt in Operations Research domain. This paper presents a new Rough Interval Max Algebra Approach (RIMAA) for solving the traffic problem with Rough Interval data. The proposed approach is simple and able to give a suitable solution to this problem. Finally, a descriptive example is given to evaluate performance of the proposed approach.

scholarly journals Dichotomized Incenter Fuzzy Triangular Ranking Approach to Optimize Interval Data Based Transportation Problem

2018 ◽  
Vol 18 (4) ◽  
pp. 111-119 ◽  
Author(s):  
Pankaj Kumar Srivastava ◽  
Dinesh C. S. Bisht
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Interval Data ◽  
Transportation Problems ◽  
Research Article

Abstract This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated with these types of problems motivates authors to tackle it by converting interval to fuzzy numbers. This confront of conversion has been achieved by proposing a dichotomic fuzzification approach followed by a unique triangular incenter ranking approach to optimize interval data based transportation problems. A comparison with existing methods is made with the help of numerical illustrations. The algorithm proposed is found prompt in terms of the number of iteration involved and problem formation. This method is practical to handle the transportation problems not having a single valued data, but data in form of a range.

scholarly journals Implementasi Algoritma Greedy Pada Pewarnaan Wilayah Kecamatan Sukodadi Lamongan

2020 ◽  
Vol 6 (2) ◽  
pp. 29-38
Author(s):  
Umi Maftukhah ◽  
Siti Amiroch ◽  
Mohammad Syaiful Pradana
Keyword(s):  
Graph Theory ◽  
Greedy Algorithm ◽  
Communication Networks ◽  
Graph Coloring ◽  
Operations Research ◽  
Dual Graph ◽  
Transportation Problems ◽  
Minimum Number ◽  
Different Color ◽  
The Greedy Algorithm

Graph theory can be applied in various fields of science such as transportation problems, communication networks, operations research, chemistry, cartography and so on. Graph theory does not only represent structure but in its application, a graph can also be colored. Many problems have graph coloring characteristics such as regional coloring. This regional coloring theory was applied to the map area of ​​Sukodadi District which consists of 20 villages. In this area coloring uses the Greedy algorithm by first making a dual graph consisting of 20 vertices and 43 edges. Based on the results of regional coloring, the minimum number of colors is 4, namely red, blue, green and yellow, with each neighboring village having a different color.

scholarly journals An Improved Vogel's Approximation Method for the Transportation Problem

2011 ◽  
Vol 16 (2) ◽  
pp. 370-381 ◽  
Author(s):  
Serdar Korukoğlu ◽  
Serkan Ballı
Keyword(s):  
Approximation Method ◽  
Operations Research ◽  
Opportunity Cost ◽  
Transportation Problem ◽  
Large Scale ◽  
Efficient Solutions ◽  
Important Task ◽  
Computational Experiments ◽  
Optimal Solutions ◽  
Transportation Problems

Determining efficient solutions for large scale transportation problems is an important task in operations research. In this study, Vogel’s Approximation Method (VAM) which is one of well-known transportation methods in the literature was investigated to obtain more efficient initial solutions. A variant of VAM was proposed by using total opportunity cost and regarding alternative allocation costs. Computational experiments were carried out to evaluate VAM and improved version of VAM (IVAM). It was seen that IVAM conspicuously obtains more efficient initial solutions for large scale transportation problems. Performance of IVAM over VAM was discussed in terms of iteration numbers and CPU times required to reach the optimal solutions.

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