A demand‐responsive feeder service with a maximum headway at mandatory stops
IF 1.6
4区 计算机科学
Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
引用次数: 0
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.一种需求响应式支线服务，在强制停靠站提供最大车头距
郊区或农村地区的公共交通至关重要。支线运输服务通过将乘客运送到有更多公共交通选择的地区来提供解决方案。一方面，完全灵活的需求响应支线服务（DRFS）有效地根据乘客的需求定制服务。另一方面，传统的支线服务提供了可预测性和更容易的成本控制。在本文中，考虑了一种半灵活的DRFS，它结合了传统服务和完全灵活服务的积极特点。这种接驳服务有两种类型的公交车站：强制性公交车站和可选公交车站。强制性公交车站保证在一定的时间间隔内有公交车到达。只有当附近有交通需求时，才可选择停靠。使用一种新型的元启发式框架（我们称之为参数空间搜索）来优化这种馈线服务的性能。在小型基准实例上的实验结果表明，启发式算法的平均性能比商业优化求解器LocalSolver高12.42%，平均运行时间为2.1s。大型实例也可以求解，通常在2分钟内求解。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
求助全文
约1分钟内获得全文
求助全文
来源期刊
Networks
工程技术-计算机：硬件
CiteScore
4.40
自引率
9.50%
发文量
46
审稿时长
12 months
期刊介绍：
Network problems are pervasive in our modern technological society, as witnessed by our reliance on physical networks that provide power, communication, and transportation. As well, a number of processes can be modeled using logical networks, as in the scheduling of interdependent tasks, the dating of archaeological artifacts, or the compilation of subroutines comprising a large computer program. Networks provide a common framework for posing and studying problems that often have wider applicability than their originating context.
The goal of this journal is to provide a central forum for the distribution of timely information about network problems, their design and mathematical analysis, as well as efficient algorithms for carrying out optimization on networks. The nonstandard modeling of diverse processes using networks and network concepts is also of interest. Consequently, the disciplines that are useful in studying networks are varied, including applied mathematics, operations research, computer science, discrete mathematics, and economics.
Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally efficient network algorithms, and innovative case studies of successful network applications. We do not typically publish works that fall in the realm of pure graph theory (without significant algorithmic and modeling contributions) or papers that deal with engineering aspects of network design. Since the audience for this journal is then necessarily broad, articles that impact multiple application areas or that creatively use new or existing methodologies are especially appropriate. We seek to publish original, well-written research papers that make a substantive contribution to the knowledge base. In addition, tutorial and survey articles are welcomed. All manuscripts are carefully refereed.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
