基于PSO-OBL算法的平面移动类立体车库车辆调度优化模型
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1.重庆交通大学;2.重庆交通大学 交通运输学院;3.浙江大学城乡规划设计研究院有限公司;4.School of Geography and Planning,Cardiff University,Cardiff,CF WA,UK

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U491.7

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国家留学基金(202208500105);中交长江建设集团发展有限公司机械式立体停车库运营风险分析及防范对策研究科研项目(E1240067)


Optimization Model for Vehicle Scheduling in Horizontal Shifting Mechanical Parking Garagebased on PSO-OBL Algorithm
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1.重庆交通大学;2.College of Traffic &3.Transportation,Chongqing Jiaotong University,Chongqing;4.Zhejiang University Urban — Planning Design Institute Co,Ltd;5.School of Geography and Planning,Cardiff University,Cardiff,CF WA,UK

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    摘要:

    针对平面移动类立体车库在车辆存取效率方面的瓶颈问题,本文提出一种基于PSO-OBL算法的存取车辆调度优化模型。该模型旨在通过精确调控车辆存取策略和时间管理,缩短车辆存取运行时间及用户平均等待时间。为提升传统粒子群算法的寻优效能和收敛速率,本文创新性地将粒子间相互协作与信息交流机制融入算法框架,并结合反向学习机制以实现问题的高效求解。实验数据表明,与传统粒子群算法相比,PSO-OBL算法在顾客平均等待时间、平均服务时间、平均等待队长以及平均运行能耗等方面均实现了显著提升,本文研究成果将为平面移动类立体车库的存取效率提供优化理论支持和实践参考。

    Abstract:

    To address the bottleneck issues in vehicle access efficiency for horizontal shifting mechanical parking garages, an access vehicle scheduling optimization model based on the PSO-OBL algorithm is proposed in this study. The model aims to shorten vehicle access operation time and reduce user average waiting time by precisely controlling vehicle access strategies and time management. To enhance the optimization performance and convergence rate of the traditional particle swarm optimization algorithm, an innovative approach incorporating inter-particle collaboration and information exchange mechanisms is embedded into the algorithm framework, along with the integration of an opposition-based learning mechanism for efficient problem-solving. Experimental data indicate that, compared to the traditional particle swarm optimization algorithm, the PSO-OBL algorithm achieves significant improvements in customer average waiting time, average service time, average queue length, and average energy consumption. The findings of this study are expected to provide theoretical support and practical reference for optimizing access efficiency in horizontal shifting mechanical parking garages.

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曾超,杨子涵,崔子豪,等. 基于PSO-OBL算法的平面移动类立体车库车辆调度优化模型[J]. 科学技术与工程, , ():

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  • 收稿日期:2023-11-22
  • 最后修改日期:2024-06-21
  • 录用日期:2024-06-24
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