Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences


Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Series Vol. 5 , 31 May 2023


Open Access | Article

Review of application on improved ant colony algorithm

Zihan Ding * 1
1 Overseas Education Institute, Nanjing Tech University, Nanjing, Jiangsu, China, 210000

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 5, 23-27
Published 31 May 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Zihan Ding. Review of application on improved ant colony algorithm. ACE (2023) Vol. 5: 23-27. DOI: 10.54254/2755-2721/5/20230518.

Abstract

A heuristic global optimization algorithm is the Ant colony algorithm, with several advantages, such as robustness, so the algorithm can be used in many fields of our daily life. This article briefly explains some of the principles of the basic ant colony algorithm, and a detailed analysis of the representative improved algorithm models, is carried out. Moreover, the research status of Ant Colony Algorithm in several fields, like travelling salesman problem, path planning problem, routing problem are also summarized in this paper.

Keywords

ant colony algorithm, path planning, assignment, routing

References

1. ZHANG Heng, HE Li, YUAN Liang, et.al. Path planning of mobile robot based on improved double layer ant colony algorithm [J]. Control and decision making, 2022, 37(2): 303-313.

2. LI Guangming, FU Jianfeng. Research on dynamic recommendation model based on user search state [J]. Information theory and Practice, 2021, 44(7): 166-172.

3. WAN JIE, GENG LI, TIAN ZHE. Multi-objective vehicle routing of fresh agricultural products based on improved ant colony algorithm [J]. Logistics and supply chain management, 2019.

4. LIU Hui, DAI Xuewu, CUI Dongliang, et.al. Optimization of high-speed train operation scheduling based on parameter adaptive ant colony algorithm [J]. Control and decision making, 2021, 36(7): 1582-1591.

5. YI Yanan, ZHEN Ran, WU Xiaojing, et.al. Adaptive multi heuristic ant colony algorithm for UAV path planning [J]. Journal of Hebei University of science and technology, 2021, 42(1): 38-47.

6. LIU Ziyu, ZHAO Lixia, XUE Jianyue, et.al. Research on vehicle routing problem based on improved ant colony algorithm [J]. Journal of Hebei University of Science and Technology, 2022, 43(1): 80-89.

7. WANG Qing, HUANG Huixia, LIU Min. Research on task assignment and scheduling of knowledge workers based on an improved ant colony algorithm [J]. 2012.

8. YIN Xiaofeng, LIU Chunhuang. Research on ant colony algorithm for quadratic assignment problem [J]. Railway Transport and Economy, Beijing, 2005.

9. CAI Jiwei, JIA Yunxian, SUN Xiao, et.al. Application of Ant Colony Algorithm to Urgent Rush-repair Assignment Problem of the Damaged Equipment [J]. 2012.

10. ZHANG Tao, HU Jiayan, LI Fujuan, et.al. Ant Colony Algorithm based on the ASRank and MMAS for the Aircraft Assignment Problem [J]. Shanghai, 2012.

11. LIU Zhibin, ZHAO Xinran. Dynamic optimization of AODV routing protocol in mobile ad hoc network based on ant colony algorithm [J]. Beijing, 2022.

12. SHANG Li, CHEN Ming, YANG Wei, et.al. Electric power communication network routing strategy based on an improved ant colony algorithm [J]. 2021.

13. WANG Hanming. Improved ant colony algorithm in computer Network routing simulation research [J]. Chongqing University of Posts and Telecommunications School of Advanced Manufacturing Engineering, Chongqing, 2020.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
ISBN (Print)
978-1-915371-57-7
ISBN (Online)
978-1-915371-58-4
Published Date
31 May 2023
Series
Applied and Computational Engineering
ISSN (Print)
2755-2721
ISSN (Online)
2755-273X
DOI
10.54254/2755-2721/5/20230518
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated