Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro

For most ultralong bus lines, low punctuality rates and vehicle bunching are two main challenges. One potential strategy to solve these two problems is to split an ultralong line into two or three shorter lines according to historical passenger flow patterns as well as other presetting objectives and constraints. Thus, in this paper, a multiobjective optimization model is first established in consideration of both passenger flow distribution and coline metro networks. Then, the optimal truncated stop is determined by estimating the model results generated by enumerating each potential bus stop derived from related metro stops. The nondominated sorting genetic algorithm II (NSGA-II) is applied to solve the model efficiently. A case study conducted on a real bus line associated with metro networks in Beijing, China, demonstrates the efficiency of the optimization strategy adoption in terms of operating cost and passenger travel time, even with a slight increase in passenger cost. Besides, the multivehicle type is also referred in the experiments to verify economic efficiency to reduce operational costs.

Section: Bus Line Optimization Combined With Metro Networkmentioning

confidence: 99%

An Optimization Strategy for Truncating Ultralong Bus Lines Integrated with Metro Networks

Song,

Chen,

2024

“…To mitigate the potential impact of multicollinearity on the estimation results, variables that exhibit strong correlations are excluded from the analysis. Figure 3 presents the Pearson coefcients for all variables evaluated on the basis of equation (3). Te darker color block indicates Cargo volume by all modes of transportation Million ton a higher linear correlation.…”

Section: Data Descriptionmentioning

confidence: 99%

“…High-speed railways (HSR) have earned widespread recognition as a fast, safe, and comfortable intercity transportation mode [1]. Tis transit form signifcantly improved the overall travel satisfaction for passengers [2,3]. Over the past decade, the mainland of China has witnessed a notable surge in the development of HSR.…”

Section: Introductionmentioning

confidence: 99%

The Impacts of High-Speed Railway on Urban GDP and Its Agglomeration: Evidence from China

Li,

Guo,

Geng

et al. 2023

This study develops difference-in-differences (DID) models to examine the direct and indirect effects of high-speed railway (HSR) operation on the urban gross domestic product (GDP) and its agglomeration. The period from 2010 to 2019 is selected as the study period, and 30 HSR-operating cities across the Chinese mainland are chosen as the study sites to be investigated. Individual fixed effects and time fixed effects are introduced to panel data models to account for the heterogeneities between cities and the endogeneities of explanatory variables. Estimation results suggest that the operation of HSR can improve the development of the urban GDP by accelerating the migration of population to HSR-operating cities, promoting the upgrading of the urban industrial structure, and improving the level of urban scientific research. Moreover, the level of urban economic agglomeration can also be improved as a result of HSR. However, the ability of HSR-promoting economic development is more significant in cities with more developed economies. Therefore, when formulating a sensible plan for the development of HSR, policymakers should prioritize the construction of HSR in more developed cities.

Bilevel Optimization of Regular Bus‐Subway‐Shared Bicycle Cooperative Operation considering Dual Uncertainties

Xue,

He,

et al. 2024

The primary objective of this paper is to minimize the overall travel costs for passengers while simultaneously maximizing the operational revenue for the transportation company. This is achieved through the optimization and adjustment of various factors, such as the intervals between regular bus and subway services, the duration of vehicle stops at each station, and the pricing structure for subway and shared bicycle usage. By enhancing the efficiency of passenger travel, we have successfully bolstered the company’s operational profits. In contrast to prior research, this paper comprehensively considers the dual uncertainties associated with both bus operations and shared bicycle operations within a cooperative system. By establishing a coordinated dual‐level optimization model for regular bus, subway, and bike‐sharing networks under dual uncertainty conditions, we employed convex combination techniques to unify the dual uncertain variables into a single objective, which was then incorporated into a chance‐constrained bilevel programming model. Ultimately, we utilized KKT conditions to transform the model from a bilevel to a single level for resolution. This paper centers its research on the collaborative system comprising the Nanchang Metro Line 1, Bus Route 520, Bus Route 211, and the adjacent region hosting a cluster of shared bicycles. By leveraging Python programming, optimization models, empirical data on traffic flow and stoppage times, and OD data, we conducted an optimization analysis to solve the problem at hand. According to the optimization results, passenger waiting time, passenger transfer time, and passenger on board time are effectively reduced by 6.81%, 18.29%, and 23.92%. At a confidence level of 95%, the resulting time level results in a 12.44% reduction in total travel time. The average subway fare increased by 18.12%, the average shared bicycle fare decreased by 19.12%, and the total cost of travel expenses increased by 16.68%. The final total cost of travel was reduced by 4.06%, and the business operating income was increased by 13.10%. The comprehensive optimization results have effectively fulfilled the objectives of the bilevel optimization model, thereby confirming the rationality and practicality of the optimization approach. The research outcomes hold significant practical implications for facilitating the efficient and cooperative development of urban transportation networks, ultimately enhancing the convenience of residents’ travel experiences.