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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 1
171-176

Traffic flow optimization bloat control genetic programming algorithm

Hu Xiaomin
Duan Yuhui
Ou Weibiao
Huang Jiawen
Lin Xiaoman
Li Min
School of Computer Science & Technology, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2024.05.0177

Abstract

In addressing the issue of increasing individual average size with iterations of the GP algorithm for training hyper-heuristic strategies in dynamic traffic assignment, this paper proposed various methods for bloat control in GP to constrain the genetic inheritance of large-sized individuals within the population. This enabled the algorithm to discover smaller-sized yet higher-performing hyper-heuristic strategies during the training process. Considering the potential performance differences of hyper-heuristic strategies on various structured road networks such as grid, ring radial, and free style networks, this paper adopted different structured road networks to train hyper-heuristic strategies for analysis and comparison. The trained hyper-heuristic strategies underwent simulation testing on urban road networks of varying scales and traffic volumes. The conclusion is that the double tournament bloat control method performs the best for different structured road networks. The GP algorithm obtained from this study demonstrates its ability to achieve shorter overall average travel times for road networks compared to existing dispatch methods. Consequently, more concise and effective hyper-heuristic strategies are derived, leading to enhanced decision-making efficiency.

Foundation Support

国家自然科学基金资助项目(62272108)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.05.0177
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 1
Section: Algorithm Research & Explore
Pages: 171-176
Serial Number: 1001-3695(2025)01-024-0171-06

Publish History

[2025-01-05] Printed Article

Cite This Article

胡晓敏, 段宇晖, 欧炜标, 等. 交通流优化膨胀控制遗传规划算法 [J]. 计算机应用研究, 2025, 42 (1): 171-176. (Hu Xiaomin, Duan Yuhui, Ou Weibiao, et al. Traffic flow optimization bloat control genetic programming algorithm [J]. Application Research of Computers, 2025, 42 (1): 171-176. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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