| Autor: |
Wahyuningsih, Sapti, Octoviana, Lucky Tri, Qohar, Abd |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3235 Issue 1, p1-7, 7p |
| Abstrakt: |
Traffic density on a road will have an impact on road congestion problems. Congestion of a road is related to the flow of vehicles passing through, the width of the road, and the maximum volume of vehicles that can pass through the road. This problem in the application of graph theory can be analyzed by network flow. Maximum flow problem as a study of network flow problems to find the maximum current that can flow on a network that has only one source and sink. In this article, we will examine the performance of the maximum flow algorithm and its application to traffic density problems. Several algorithms that can be used to solve the maximum flow problem are the Ford Fulkerson algorithm or the augmenting path algorithm, the Edmons Karp algorithm and the Dinitz algorithm. In Ford Fulkerson's algorithm there is no setting for selecting the adding path, whereas in the Edmons Karp algorithm, the selected adding path is the shortest adding path. The Dinitz algorithm is better than the Ford-Fulkerson algorithm and the Edmond-Karp algorithm because the time required for the execution of the Ford-Fulkerson algorithm and the Edmond-Karp algorithm is relatively larger than the Dinitz algorithm. In this article, examples of applications using algorithms for solving maximum flow problems with software tools are given. In the analysis of data on the flow of vehicles on the road, the road segment experiences traffic density if the road segment has a capacity value that is smaller than the flow of vehicles. The degree of road saturation (DS) is the ratio between vehicle traffic and road capacity. Several roads in Malang city have a high degree of saturation (DS) (> 0.8), which means they experience congestion. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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