Optimizing Departure Interval for Bus Dispatching System Based on Comprehensive Objective Model

Zhu, Xue-Wu; Meng, Xianfen; Zhang, Mengmeng

doi:10.1061/9780784413623.122

Cited by 3 publications

(1 citation statement)

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“…On the other hand, it can maximize vehicle resources and save costs for bus companies. For example, Zhu et al [29] proposed a departure interval optimization model to optimize the departure intervals of public transit. In this study, the departure interval refers to [29] is 8 minutes.…”

Section: Experimental Data Previous Figurementioning

confidence: 99%

Flexible Scheduling Model of Bus Services between Venues of the Beijing Winter Olympic Games

Zhang

Huang

Jiang

et al. 2022

Journal of Advanced Transportation

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Traditional buses travel on fixed routes and areas, which cannot satisfy the flexible demands of athletes in the context of COVID-19 and the closed-loop traffic management policy during the 2022 Beijing Winter Olympic Games (BWOG). This study predicts the travel demands based on the characteristics of athletes’ daily travel demands and then presents a flexible bus service scheduling model for cross-region scheduling among Beijing, Yanqing, and Zhangjiakou to provide high-level service. The flexible bus service is point-to-point and avoids unnecessary contact, which reduces the risk of spreading COVID-19 and ensures athletes’ safety. In this study, the flexible bus scheduling model is established to optimize scheduling schemes, whose object is to minimize the cost of the system based on some realistic constraints. These constraints consider not only the preferred time windows of athletes’ demand but also the vehicle’s capacity, depot, minimum load factor, total demands, etc. In addition, a genetic-simulated annealing hybrid algorithm (GSAHA) is designed to solve the model based on the characteristics of the genetic algorithm (GA) and simulated annealing. To assess the feasibility and efficiency of the model and algorithm, a case study is conducted in the Beijing-Yanqing area. Furthermore, the travel time of the flexible bus is compared to that of the traditional bus, according to the results of the case study. Moreover, the sensitivity of the model and algorithm are analyzed. The experimental results show that the proposed model and algorithm can dispatch buses with superior flexibility and high-level services during the BWOG.

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Section: Experimental Data Previous Figurementioning

confidence: 99%