Optimizing customized bus services for multi-trip urban passengers: A bi-objective approach

IF 2.3 4区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IET Intelligent Transport Systems Pub Date : 2024-10-04 DOI:10.1049/itr2.12569

Yunlin Guan, Yun Wang, Haonan Guo, Xiaobing Liu, Xuedong Yan

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Abstract

Customized bus services typically focus on single-trip requests, which often struggle to accommodate the growing needs for varied multiple trips in urban daily travel. This paper addresses the customized bus routing problem for passengers with multiple trips. A bi-objective mathematical model is established for maximizing the operational profit and minimizing the travel costs by considering the characteristics of the multi-trip requests and time-dependent travel time. Besides, a novel profit objective function is proposed considering the service's completion status and the starting price. Since the proposed mixed integer linear programming model is an NP-hard problem, a non-dominated sorting genetic algorithm II-based method is proposed to handle different sizes of instances. Finally, the instances with multi-trip requests are carried out to test the accuracy of the model and the effectiveness of our method compared with Gurobi and the local search-based multi-objective algorithm approach.

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为多趟城市乘客优化定制公交服务：双目标方法

定制公交服务通常以单次出行需求为主，往往难以满足城市日常出行中日益增长的多次出行需求。本文探讨了乘客多次出行的定制公交路线问题。考虑到多趟出行请求的特点和随时间变化的出行时间，建立了一个双目标数学模型，以实现运营利润最大化和出行成本最小化。此外，考虑到服务的完成状态和起始价格，还提出了一个新的利润目标函数。由于所提出的混合整数线性规划模型是一个 NP 难问题，因此提出了一种基于非支配排序遗传算法 II 的方法来处理不同规模的实例。最后，通过多行程请求实例来检验模型的准确性，以及我们的方法与 Gurobi 和基于局部搜索的多目标算法方法相比的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IET Intelligent Transport Systems 工程技术-运输科技

CiteScore

6.50

自引率

7.40%

发文量

159

审稿时长

3 months

期刊介绍： IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf