基于改进自适应大邻域算法的公交线网规划方法

doi:10.16097/j.cnki.1009-6744.2023.05.010

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (5): 96-103.DOI: 10.16097/j.cnki.1009-6744.2023.05.010

基于改进自适应大邻域算法的公交线网规划方法

李光春，聂磊^*

北京交通大学，交通运输学院，北京 100044

收稿日期:2023-03-26 修回日期:2023-05-23 接受日期:2023-06-05 出版日期:2023-10-25 发布日期:2023-10-22
作者简介:李光春(1980- )，男，云南普洱人，博士生。
基金资助:
国家自然科学基金联合基金 (U1934216)；国铁集团重点课题(N2020X023)；国铁集团重大课题(K2022X029)。

Bus Network Planning Method Based on Improved Adaptive Large Neighborhood Search Algorithm

LI Guang-chun,NIE Lei^*

School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Received:2023-03-26 Revised:2023-05-23 Accepted:2023-06-05 Online:2023-10-25 Published:2023-10-22
Supported by:
Joint Funds of the National Natural Science Foundation of China (U1934216)；Key Project of China National Railway Group Limited (N2020X023)；Key Project of China National Railway Group Limited (K2022X029)。

摘要/Abstract

摘要： 面向城市中大规模线网规划问题，本文提出一种基于改进自适应大邻域算法的公交线网规划方法。该方法首先缩减问题规模，将大量乘客出行OD(Origin-Destination)合并获得城市公交备选站点；综合考虑线网服务客流量、公交站点覆盖率和线路服务效率等优化目标，线网长度、非直线系数、线路换乘等限制条件，分别建立以服务需求/延展换乘为主要功能的主线/支线公交线网规划模型；在OD合并结果基础上设计改进自适应大邻域算法进行问题求解，该方法含改进的8种邻域算子和自适应规则等。案例分析结果表明：本文两阶段算法整体优化效果明显，改进自适应大邻域算法领先现有其他元启发算法；邢台市实际案例计算结果表现良好，该方法能有效解决较大规模线网规划问题。

关键词: 城市交通, 公共交通, 公交线网规划, 节点合并算法, 自适应大邻域算法

Abstract: This paper proposes a bus network planning method based on an improved adaptive large neighborhood search algorithm for the large scale network. The method is able to reduce the scale of problems, merge the OD(OriginDestination) of passengers, and select bus stops. The study develops the main line and branch line models considering the optimization objectives of passenger demand and bus station coverage, and the constraints of network length, nonlinear coefficient and transfer. Based on the results of the node merging algorithm, the improved adaptive large neighborhood algorithm is used to solve the problem, including eight improved operators and adaptive rules. The case analysis indicated that the two- stage algorithm performs well, and the improved adaptive large neighborhood algorithm performs better than existing meta-heuristic algorithms. The case analysis in Xingtai has shown good performance and can effectively solve large-scale network planning problems.

Key words: urban traffic, public transit, bus network planning, OD merging algorithm, adaptive large neighborhood search

中图分类号:

U412.1

李光春, 聂磊. 基于改进自适应大邻域算法的公交线网规划方法[J]. 交通运输系统工程与信息, 2023, 23(5): 96-103.

LI Guang-chun, NIE Lei. Bus Network Planning Method Based on Improved Adaptive Large Neighborhood Search Algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 96-103.

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基于改进自适应大邻域算法的公交线网规划方法

Bus Network Planning Method Based on Improved Adaptive Large Neighborhood Search Algorithm

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