Research on Expressway Emergency Vehicle Allocation Based on Improved Particle Swarm Optimization

被引:2
|
作者
Wu, Lieyang [1 ]
机构
[1] Jiangxi Expressway Networking Management Ctr, Nanchang 330036, Jiangxi, Peoples R China
来源
关键词
Particle swarm optimization; Population diversity; Expressway; The allocation of emergency vehicles;
D O I
10.1007/978-3-319-48490-7_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Firstly, an improved particle swarm optimization algorithm is proposed to solve the allocation of expressway emergency vehicles. Compared with the standard PSO algorithm, the particle population number of the improved PSO algorithm is increased, due to particle flight behavior of different populations is different and particle information between different populations is exchanged, so the swarm population diversity of the improved PSO algorithm is increased, and its ability to jump out of local optimum is improved. Moreover, the improved algorithm is applied to the allocation of emergency vehicles, that is, the mathematical model is established to solve the shortest travel distance of the emergency vehicle, and the mathematical model is optimized by the proposed algorithm to obtain the optimal solution. The experimental results show that the improved algorithm proposed in this paper is feasible and effective to solve the expressway emergency vehicle allocation problem.
引用
收藏
页码:139 / 145
页数:7
相关论文
共 50 条
  • [1] Particle Swarm Optimization Algorithm for Emergency Resource Allocation on Expressway
    Gan, Chai
    Ying-ying, Sun
    Cang-hui, Zhu
    WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09), 2009, : 135 - 139
  • [2] Research of Emergency Logistics Routing Optimization Based on Particle Swarm Optimization
    Zhang, Liyi
    Li, Yang
    Fei, Teng
    Chen, Xi
    Ting, Guo
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (CSAIT 2013), 2014, 255 : 415 - 421
  • [3] Emergency Response Resource Allocation in Sparse Network Using Improved Particle Swarm Optimization
    Zhang, Yongqiang
    Hu, Zhuang
    Zhang, Min
    Ba, Wenting
    Wang, Ying
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (16)
  • [4] Multirobot task allocation based on an improved particle swarm optimization approach
    Zhu, Zhanxia
    Tang, Biwei
    Yuan, Jianping
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2017, 14 (03):
  • [5] Allocation of Distributed Generations Based on Improved Particle Swarm Optimization Algorithm
    Liu Wei
    Zhang Haiyan
    PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 1242 - 1245
  • [6] Study on vehicle scheduling problem based on improved particle swarm optimization
    Wang Fei
    SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS II, PTS 1 AND 2, 2014, 475-476 : 710 - 714
  • [7] Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm
    Zou, Zeyu
    Zeng, Hui
    Zheng, Xiaodong
    Chen, Junming
    MATHEMATICS, 2025, 13 (04)
  • [8] Research on Image Processing Based on Improved Particle Swarm Optimization
    Wang, RuiYing
    2018 10TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA), 2018, : 538 - 540
  • [9] Research on Knowledge Acquisition based on Improved Particle Swarm Optimization
    Chen, Xiu Hai
    Jia, Jun Bo
    Li, Xu Yuan
    Wang, Shi Ke
    Zhao, Ye
    FRONTIERS OF MANUFACTURING SCIENCE AND MEASURING TECHNOLOGY III, PTS 1-3, 2013, 401 : 1539 - +
  • [10] Research on Feature Selection based on Improved Particle Swarm Optimization
    Wang, Guo Qing
    Jia, Jun Bo
    Li, Xu Yuan
    MANUFACTURING ENGINEERING AND AUTOMATION II, PTS 1-3, 2012, 591-593 : 2651 - +