Optimization Method of Combined Multi-Mode Bus Scheduling under Unbalanced Conditions

Dalong Li, Benxing Liu, Fangtong Jiao, Ziwen Song, Pengsheng Zhao, Xiaoqing Wang and Feng Sun ()
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Dalong Li: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Benxing Liu: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Fangtong Jiao: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Ziwen Song: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Pengsheng Zhao: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Xiaoqing Wang: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Feng Sun: School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China

Sustainability, 2022, vol. 14, issue 23, 1-17

Abstract: In view of the spatial and temporal imbalance of residents’ travel demands and challenges of optimal bus capacity allocation, in this paper the grand station express bus scheduling mode is introduced in the direction of heavy passenger flow during peak hours. Coordinated scheduling combining whole-journey and grand station express buses is adopted, and the station correlation calculation model is used to determine the optimal stops of the grand station express bus. Thus, a two-way bus scheduling optimization model for peak passenger flow is established with the goal of minimizing the total cost of passenger travel and enterprise operation. Finally, the nonlinear inertia weight dynamic cuckoo search algorithm is selected for the model’s solution, and the established scheduling optimization model is solved by combining basic data such as the study line’s bus Integrated Circuit (IC) card data. The effectiveness of the model is verified through a comparative study and evaluation of the solution.

Keywords: unbalanced conditions; combined optimal scheduling; cuckoo search algorithm; bus IC card data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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