Abstract
The problem of public transportation routes network design deals with establishing the configuration of transit routes in a transportation network. This problem is recognized as one of the most complicated problems in transportation planning. An appropriate design of transit network will help increasing transit share of urban trips and reducing traffic congestion in urban networks. Previous research proposed the Route Generation Algorithm (RGA) in which shortest paths with the highest demands are selected and then expanded by insertion of new nodes in order to increase transit demand coverage. This paper extends RGA by introducing a new algorithm namely Extended Route Generation Algorithm (ERGA) with further details in node insertion scheme. A heuristic algorithm is proposed, tested in a medium-size network, and applied on a real-size network. In contrast to the conventional RGA in which all nodes are examined to be inserted between nodes of Origin-Destination (O-D) pairs, the algorithm inserts only adjacent nodes to the shortest paths between selected (O-D) pairs. Moreover, the proposed algorithm restricts the distance between each pair of nodes, not to be greater than two times of the shortest path length between the two nodes and the travel time of each generated route in the problem. Also, the number of common links between proposed routes of ERGA has been restricted due to the specifications of case study network.
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The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The authors gratefully acknowledge the contributions of Aavand Consulting Engineers Company for generously providing data and reports of the comprehensive transportation studies of Ardebil city.
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Khanzad, I., Seyedabrishami, S., Nazemi, M., Zarrinmehr, A. (2018). Transit Network Design Problem: An Expansion of the Route Generation Algorithm. In: Żak, J., Hadas, Y., Rossi, R. (eds) Advanced Concepts, Methodologies and Technologies for Transportation and Logistics. EURO EWGT 2016 2016. Advances in Intelligent Systems and Computing, vol 572. Springer, Cham. https://doi.org/10.1007/978-3-319-57105-8_8
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