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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 6

Research on TSP problem of urban modeling based on pheromone matrix optimization ant colony algorithm

Liu Daia,b
Zhang Yaminga,b
Wang Kaia,b
Cui Haiqinga,b
a. Faculty of Electronic Information & Automation, b. Engineering Technology Training Center, Civil Aviation University of China, Tianjin 300000, China
DOI: 10.19734/j.issn.1001-3695.2024.11.0444

Abstract

This paper proposes an optimized ant colony algorithm to address the Traveling Salesman Problem (TSP) in urban modeling. The algorithm integrates random averaging of the pheromone matrix, adaptive perturbation, and dynamic proportional resetting strategies to optimize the path search in the process of acquiring urban modeling materials. After each round of path selection, the algorithm globally updates the local pheromone based on the quality of the paths and accelerates convergence through 2-opt optimization. Initially, the random averaging strategy is applied. When the optimal path has not been updated for multiple iterations, the pheromone of random nodes is averaged to avoid local optima. When multiple attempts at the random averaging strategy prove ineffective, the adaptive perturbation strategy is introduced. This strategy perturbs the pheromone matrix to select paths, thereby reducing the risk of local optima. This strategy perturbs the pheromone matrix to select paths, reducing the risk of local optima. When the quality of the optimal path decreases by a certain proportion, the dynamic proportional resetting strategy is used to increase the difference between high and low pheromone values in the matrix, further accelerating convergence. The results show that the algorithm effectively improves global search capability, accelerates the convergence process, and provides a solution to the TSP in urban modeling.

Foundation Support

中央高校基本科研业务费项目(3122025079)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.11.0444
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 6

Publish History

[2025-03-10] Accepted Paper

Cite This Article

刘岱, 张亚鸣, 王凯, 等. 基于信息素矩阵优化蚁群算法求解城市建模的旅行商问题 [J]. 计算机应用研究, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0444. (Liu Dai, Zhang Yaming, Wang Kai, et al. Research on TSP problem of urban modeling based on pheromone matrix optimization ant colony algorithm [J]. Application Research of Computers, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0444. )

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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