带接送和时间窗口的定制公交路线设计:模型、案例研究和对比分析

IF 7.5 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Expert Systems with Applications Pub Date : 2021-04-15 DOI:10.1016/j.eswa.2020.114242
Xi Chen , Yinhai Wang , Yong Wang , Xiaobo Qu , Xiaolei Ma
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引用次数: 28

摘要

定制巴士(CB)是一种新兴的公共交通系统,它不仅提供了灵活可靠的需求响应服务,还减少了私家车的使用,以缓解大都市的交通拥堵。定制公交线路设计问题(CBRDP)是CB服务系统设计中的一个关键环节。在这项工作中,我们开发了一种新型的问题场景:带时间窗口的多次接送问题,通过同时优化运营成本和乘客利润来描述CBRDP,其中引入额外的旅行时间来估计乘客与出租车服务相比的额外成本,并允许每辆车进行多次旅行以节省运营成本。为了解决这个问题,提出了一种构造性的两阶段启发式算法来获得Pareto解。以一个基准问题和北京通勤走廊为例,我们计算并比较了CB与其他出行方式的货币和出行成本,并定量地证实了CB是乘客的一个具有成本效益的选择。
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Customized bus route design with pickup and delivery and time windows: Model, case study and comparative analysis

The customized bus (CB) is an emerging type of public transportation system, which not only provides a flexible and reliable demand-responsive service, but also reduces the usage of private car to alleviate traffic congestion in metropolitan cities. The customized bus route design problem (CBRDP) is a crucial procedure in the CB service system designing. In this work, we develop a new type of problem scenario: Multi-Trip Multi-Pickup and Delivery Problem with Time Windows, to describe CBRDP by simultaneously optimizing the operating cost and passenger profit, where excess travel time is introduced to estimate passenger extra cost compared with taxi service, and each vehicle is allowed to perform multiple trips for operational cost savings. To solve this problem, a constructive two-stage heuristic algorithm is presented to obtain the Pareto solution. Taking a benchmark problem and Beijing commuting corridor as case studies, we calculate and compare the monetary and travel costs of CB with other travel modes, and quantitatively confirm that the CB can be a cost-effective choice for passengers.

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来源期刊
Expert Systems with Applications
Expert Systems with Applications 工程技术-工程:电子与电气
CiteScore
13.80
自引率
10.60%
发文量
2045
审稿时长
8.7 months
期刊介绍: Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.
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