|Table of Contents|

Intelligent optimization method for highway route corridor belt based on particle swarm optimization(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2025年2期
Page:
14-23
Research Field:
道路工程
Publishing date:

Info

Title:
Intelligent optimization method for highway route corridor belt based on particle swarm optimization
Author(s):
JIA Xing-li;  XIAO Zhan;  GUO Jun-heng;  FU Yu-jia;  DENG Yu
(School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China)
Keywords:
road engineering;  route corridor belt;  intelligent route selection;  particle swarm optimization;  fitness function
PACS:
U412.3
DOI:
10.19721/j.cnki.1671-8879.2025.02.002
Abstract:
To improve the efficiency of multi-objective decision-making for highway route corridor belt, the automatic updating mechanism of route spatial position under coupling constraints was explored. Firstly, based on the theory of particle swarm optimization(PSO), the connotation of relative spatial position oriented to the spatial curve characteristics of highway route corridor belt was defined. The staged-reallocation dynamic updating method of relative spatial position was proposed. The intelligent optimization method for highway route corridor belt was constructed based on PSO. Secondly, the highway route selection constraint factor system including topography, geology, hydrology, environment and land occupation was screened and established. Considering the interaction between route and constraint factors, the function expressions of topography fitness and cost fitness were solved, respectively, and the intelligent optimization process for highway route corridor belt was proposed. Finally, taking the river valley expressway project as an example, the intelligent generation and result analysis of the highway route scheme were carried out. The research results show that the fitness decreases significantly after 20 iterations, and remains stable after 2 000 iterations. The direction of route intersection points is updated by setting the relative spatial position, and the converted element position optimization can effectively solve the problem that the PSO tend to search in local space. The optimized route selection method shows a high fitness to the topography function and can effectively reduce the economic cost of the project. The staged-reallocation position updating method can improve the optimization ability of the model. Compared with the route scheme without reallocation, thetopography fitness increases by 1.2%, and the economic cost of the project reduces by 38.4%. Compared with the manual scheme, the cost of the optimized scheme decreases by 9.22%. The intelligent optimization method for highway route corridor belt based on PSO can balance the topography and economic cost of project, providing an important reference for manual route selection. 2 tabs, 6 figs, 28 refs.

References:

[1] 薛新功,李 伟,蒲 浩.铁路线路智能优化方法研究综述[J].铁道学报,2018,40(3):6-15.
XUE Xin-gong,LI Wei,PU Hao.Research review of intelligent optimization methods of railway alignment[J].Journal of the China Railway Society,2018,40(3):6-15.
[2]韩春华.基于GIS的铁路选线系统智能环境建模方法研究[D].成都:西南交通大学,2009.
HAN Chun-hua.Research on intelligent environment modeling method of railway line selectionsystem based on GIS[D].Chengdu:Southwest Jiaotong University,2009.
[3]袁 泉,曾文驱,李子涵.基于改进型D3QN深度强化学习的铁路智能选线方法[J].铁道科学与工程学报,2022,19(2):344-350.
YUAN Quan,ZENG Wen-qu,LI Zi-han.Intelligent railway alignment method based on improved D3QN deep reinforcement learning[J].Journal of Railway Science and Engineering,2022,19(2):344-350.
[4]HOWARD B E,BRAMMICK Z,SHAW J F.Optimum curvature principle in highway routing[J].Journal of the Highway Division,1968,94(1):61-82.
[5]SHAW J F,HOWARD B E.Comparison of two integration methods in transportation routing[J].Transportation Research Record,1981,8(6):8-13.
[6]SHAW J F B,HOWARD B E.Expressway route optimization by OCP[J].Journal of Transportation Engineering,1982,108(3):227-243.
[7]HOGANJ D.Experience with OPTLOC-optimum location of highways by computer[R].London:PTRC,1973.
[8]TRIETSCH D.A family of methods for preliminary highway alignment[J].Transportation Science,1987,21(1):17-25.
[9]詹振炎,常新生.人机交互系统铁路线路平纵面整体优化设计[J].铁道工程学报,1990(1):87-91.
ZHAN Zhen-yan,CHANG Xin-sheng.Optimization design of horizontal and vertical plane of railway line based on human-computer interaction system[J].Journal of Railway Engineering Society,1990(1):87-91.
[10]常新生,詹震炎.铁路线路平纵面整体优化设计的理论与方法[J].铁道学报,1995,17(4):75-81.
CHANG Xin-sheng,ZHAN Zhen-yan.Theory and method of the whole optimization design of railway line plane and longitudinal plane[J].Journal of Railway Engineering-Society,1995,17(4):75-81.
[11]马庆雷.基于遗传算法的公路平面优化[J].中国公路学报,2006,19(1):42-46.
MA Qing-lei.Optimization of highway plane based on genetic algorithm[J].China Journal of Highway and Transport,2006,19(1):42-46.
[12]许金良,王海君,杨少伟.基于遗传算法的公路纵断面优化[J].交通运输工程学报,2003,3(2):48-52.
XU Jin-liang,WANG Hai-jun,YANG Shao-wei.Optimization of highway longitudinal section based on genetic algorithm[J].Journal of Traffic and Transportation Engineering,2003,3(2):48-52.
[13]叶亚丽,庄传仪.公路路线多目标遗传算法优化设计研究[J].公路,2012(10):101-107.
YE Ya-li,ZHUANG Chuan-yi.Multi-objective genetic algorithm optimization design research for highway alignment[J].Highway,2012(10):101-107.
[14]张 驰,杨 坤,汪双杰,等.青藏高原多年冻土区公路智能选线方法[J].交通运输工程学报,2016,16(4):14-25.
ZHANG Chi,YANG Kun,WANG Shuang-jie,et al.Intelligent alignment method for highway in permafrost area of Qinghai-Tibet Plateau[J].Journal of Traffic and Transportation Engineering,2016,16(4):14-25.
[15]韩春华,易思蓉,杨 扬.基于最优路径分析的线路初始平面自动生成方法[J].西南交通大学学报,2011,46(2):252-258.
HAN Chun-hua,YI Si-rong,YANG Yang.Automatic generating method of initial plane based on optimal path analysis[J].Journal of Southwest Jiaotong University,2011,46(2):252-258.
[16]杨宏志,韩跃杰,李 芬,等.基于GIS和遗传算法的公路智能选线[J].长安大学学报(自然科学版),2009,29(3):48-53.
YANG Hong-zhi,HAN Yue-jie,LI Fen,et al.Highway intelligent alignment based on GIS and genetic algorithm[J].Journal of Chang'an University(Natural Science Edition),2009,29(3):48-53.
[17]夏沁雪.水电站进场道路智能选线算法及方案比选方法研究[D].武汉:华中科技大学,2022.
XIA Qin-xue.Research on intelligent route selection algorithm and scheme comparison method of approach road for hydropower station[D].Wuhan:Huazhong University of Science and Technology,2022.
[18]王月爽.基于改进A*算法的山地风电场道路智能选线方法研究[D].石家庄:石家庄铁道大学,2022.
WANG Yue-shuang.Research on intelligent road route selection method for mountain wind farm based on improved A* algorithm[D].Shijiazhuang:Shijiazhuang Tiedao University,2022.
[19]周斌科,毕静刚,杨保华,等.道路智能选线技术与方法研究[J].工程管理学报,2024,38(6):86-91.
ZHOU Bin-ke,BI Jing-gang,YANG Bao-hua,et al.Research on intelligent alignment technology and method[J].Engineering management journal,2024,38(6):86-91.
[20]陈雯琦,黄姝娟,吴霜霜,等.基于粒子群优化算法的多无人机多目标航迹路径规划[J].微电子学与计算机,2023(9):21-28.
CHEN Qi-wen,HUANG Shu-juan,WU Shuang-shuang,et al.Path planning of multi-target trajectory for multi-UAV based on particle swarm optimization algorithm[J].Microelectronics and Computer,2023(9):21-28.
[21]智瀚宇,贾新春,张学立.无人机路径规划:一种粒子群和灰狼复合算法[J].控制工程,2023,DOI:10.19304/j.ISSN1000-7180.2002.0660.
ZHI Han-yu,JIA Xin-chun,ZHANG Xue-li.UAV path planning:A particle swarm and gray wolf composite algorithm[J].Control Engineering of China,2023,DOI:10.19304/j.ISSN1000-7180.2002.0660.
[22]李锐君,董素鸽.基于粒子群算法的无人机灭火路径规划仿真[J].计算机仿真,2023,40(9):43-48.
LI Rui-jun,DONG Su-ge.Simulation of UAV fire extinguishing path planning based on particle swarm optimization algorithm[J].Computer Simulation,2023,40(9):43-48.
[23]胡章芳,冯淳一,罗 元.改进粒子群优化算法的移动机器人路径规划[J].计算机应用研究,2021,38(10):3089-3092.
HU Zhang-fang,FENG Chun-yi,LUO Yuan.Path planning of mobile robot based on improved particle swarm optimization algorithm[J].Application Research of Computers,2021,38(10):3089-3092.
[24]康 亮,徐 杨,尹丽华.一种面向群组机器人搜索任务的改进粒子群算法[J].中国科技论文,2023,18(11):1244-1249.
KANG Liang,XU Yang,YIN Li-hua.An improved particle swarm optimization algorithm for group robot search tasks[J].China Sciencepaper,2023,18(11):1244-1249.
[25]温琼阳,朱学军,李 毅,等.基于改进粒子群算法的机械臂能耗轨迹优化[J].计算机应用研究,2023,40(9):1-8.
WEN Qiong-yang,ZHU Xue-jun,LI Yi.Optimization of energy consumption trajectory of robotic arm based on improved particle swarm optimization algorithm[J].Application Research of Computers,2023,40(9):1-8.
[26]刘小红,张人龙,单汨源.基于云模型的量子混合粒子群算法及其应用[J].统计与决策,2021,37(3):54-58.
LIU Xiao-hong,ZHANG Ren-long,SHAN Mi-yuan.Quantum hybrid particle swarm optimization based on cloud model and its application[J].Statistics and Decision,2021,37(3):54-58.
[27]MOHAMMAD M,SAEED M,VAHID B.An optimization model for synchronous road geometric and pavement enhancements[J].Journal of Traffic and Transportation Engineering(English Edition),2021,8(3):421-438.
[28]王素欣,高 利,崔小光,等.交通分配的粒子群优化算法[J].交通运输工程学报,2007,7(5):97-100,122.
WANG Su-xin,GAO Li,CUI Xiao-guang.Particle swarm optimization algorithm for traffic allocation[J].Journal of Traffic and Transportation Engineering,2007,7(5):97-100,122.

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Last Update: 2025-04-01