现场多网点车辆调度方案的汇总公式

IF 8.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-04-26 DOI:10.1111/mice.13217
Yi Gao, Yuanjie Tang, Rengkui Liu
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引用次数: 0

摘要

多站点车辆调度问题(MDVSP)是公共交通领域的一项基本挑战。为了解决大规模模型问题以及传统的基于行程到行程连接的 MDVSP 方法固有的解对称性问题,我们提出了一种新的基于行程到路线(T2R)连接的方法。考虑到现实世界中的问题特点,即众多行程共享共同的起点-终点站和一条路线上的旅行时间,该方法将相同车辆可能的行程序列聚合到 T2R 连接中。构建了两种时空网络聚合(TSNA)流表述版本,即基于路线对的 TSNA 和基于车站对的 TSNA。此外,还证明了在任何给定的分解策略(包括先进先出)下,TSNA 与多商品网络流量(MCNF)模型的等价性。考虑到有利的可分离 TSNA 结构,提出了一种基于交替方向乘法(ADMM)的程序,将 MDVSP 分解为多个子问题,这些子问题可以线性化,并可使用商业求解器轻松求解。利用从拉格朗日松弛问题中获得的下限对解决方案的质量进行了评估。随后,利用随机数据集和真实世界实例证实了所提出的 MDVSP 模型和算法的有效性和优越性。
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Aggregation formulation for on-site multidepot vehicle scheduling scenario
The multidepot vehicle scheduling problem (MDVSP) is a fundamental public transport challenge. To address the large-scale model and inherent solution symmetry associated with the traditional trip-to-trip connection-based approach for MDVSP, a new trip-to-route (T2R) connection-based approach is proposed. Considering real-world problem characteristics with numerous trips sharing common origin–destination stations and travel times on one route, this approach aggregates same vehicle possible trip sequences into a T2R connection. Two time-space network aggregation (TSNA) flow formulation versions, route pair-based TSNA and station pair-based TSNA, were constructed. Furthermore, TSNA equivalence under any given decomposition strategy, including first-in-first-out, with the multicommodity network flow (MCNF) model was demonstrated. Given the favorable separable TSNA structure, an alternating direction method of multipliers (ADMM)-based procedure is proposed to decompose the MDVSP into multiple subproblems that can be linearized and readily solved using commercial solvers. The quality of the solutions was assessed using lower bounds obtained from the Lagrangian relaxation problem. The effectiveness and superiority of the proposed MDVSP models and algorithms were subsequently confirmed using random data sets and real-world instances.
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来源期刊
CiteScore
17.60
自引率
19.80%
发文量
146
审稿时长
1 months
期刊介绍: Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.
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