车头时距
公共交通
服务(商务)
计算机科学
水准点(测量)
解算器
启发式
可预测性
运筹学
数学优化
运输工程
模拟
业务
工程类
数学
营销
人工智能
统计
大地测量学
程序设计语言
地理
作者
Bryan David Galarza Montenegro,Kenneth Sörensen,Pieter Vansteenwegen
出处
期刊:Networks
[Wiley]
日期:2023-09-07
卷期号:83 (1): 100-130
被引量:6
摘要
Abstract Public transportation out of suburban or rural areas is crucial. Feeder transportation services offer a solution by transporting passengers to areas where more options for public transport are available. On one hand, fully flexible demand‐responsive feeder services (DRFSs) efficiently tailor their service to the needs of the passengers. On the other hand, traditional feeder services provide predictability and easier cost control. In this article, a semi‐flexible DRFS is considered, which combines positive characteristics of both traditional services as well as fully flexible services. This feeder service has two types of bus stops: mandatory bus stops and optional bus stops. Mandatory bus stops are guaranteed to be visited by a bus within a certain time interval. Optional stops are only visited when there is demand for transportation nearby. The performance of this feeder service is optimized with the use of a new type of metaheuristic framework, which we denote as parameter space search . Experimental results on small benchmark instances indicate that the heuristic performs on average 12.42% better than LocalSolver, a commercial optimization solver, with an average runtime of 2.1 s. Larger instances can also be solved, typically within 2 min.
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