skip to main content
10.1145/3583133.3590552acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
poster

Ant Colony Optimization with Pre-exploration of Outliers for TSP

Published: 24 July 2023 Publication History

Abstract

Constructing a finite set of candidates for each node has been proved that it is an effective means in ant colony optimization (ACO) for solving the travelling salesman problem (TSP). However, some neighbor nodes in the optimal routes are two nodes with large separation distance. To solve this problem, this paper proposes an ACO with pre-exploration of outliers (ACO-EO). The techniques in ACO-EO include: a) the outliers selection, b) pre-exploration adjacent nodes for outliers. To verify the effectiveness of the ACO-EO, a number of experiments are conducted using 30 benchmark instances (ranging from 101 nodes to 1784 nodes in topologies) taken from the well-known TSPLIB. From the comparison with state-of-the-art ACO-based methods, ACO-EO outperforms these competitors in terms of convergence and solution accurancy.

References

[1]
Merrill M. Flood. 1956. "The traveling-salesman problem." Operations Research, vol.4, no.1, 61--75.
[2]
Liu Fei and Zeng Guangzhou. 2009. "Study of genetic algorithm with reinforcement learning to solve the TSP." Expert Systems with Applications, vol.36, no.3, pt.2, 6995--7001.
[3]
JA Tenreiro Machado, Seyed Mehdi Abedi Pahnehkolaei, and Alireza Alfi. 2021. "Complex-order particle swarm optimization." Communications in Nonlinear Science and Numerical Simulation, vol.92, 105448.
[4]
Indadul Khan and Manas Kumar Maiti. 2019. "A swap sequence based artificial bee colony algorithm for traveling salesman problem." Swarm and Evolutionary Computation, vol.44, 428--438.
[5]
Li Shundong, You Xiaoming, and Liu Sheng. 2021. "Co-evolutionary multi-colony ant colony optimization based on adaptive guidance mechanism and its application." Arabian Journal for Science and Engineering, vol.46, 9045--9063.
[6]
Marco Dorigo, Vittorio Maniezzo, and Alberto Colorni. 1996. "Ant system: optimization by a colony of cooperating agents." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.26, no.1, 29--41.
[7]
Marco Dorigo and Luca Maria Gambardella. 1997. "Ant colony system: a cooperative learning approach to the traveling salesman problem." in IEEE Transactions on Evolutionary Computation, vol.1, no.1, 53--66.
[8]
Thomas Stützle and Holger H. Hoos. 2000. "MAX-MIN ant system." Future Generation Computer Systems, vol.16, no.8, 889--914.
[9]
Marcus Randall and James Montgomery. 2002. "Candidate set strategies for ant colony optimisation." International Workshop on Ant Algorithms, 243--249.
[10]
Joshua Peake, Martyn Amos, Paraskevas Yiapanis and Huw Lloyd. 2018. "Vectorized candidate set selection for parallel ant colony optimization." Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1300--1306.
[11]
Rafał Skinderowicz. 2022. "Improving ant colony optimization efficiency for solving large TSP instances." Applied Soft Computing, vol.120, 108653.
[12]
Luca Maria Gambardella, Roberto Montemanni and Dennis Weyland. 2012. "Coupling ant colony systems with strong local searches." European Journal of Operational Research, vol.220, no.3, 831--843.
[13]
Darren M. Chitty 2017. "Applying ACO to large scale TSP instances." in UK Workshop on Computational Intelligence, 104--118.
[14]
Yu Jin, You Xiaoming and Liu Sheng. 2021. "A heterogeneous guided ant colony algorithm based on space explosion and long-short memory." Applied Soft Computing, vol.113, pt.B, 107991.
[15]
Gerhard Reinelt. 1991. "TSPLIB---A traveling salesman problem library." ORSA Journal on Computing, vol.3, no.4, 376--384.
[16]
Zhong Yiwen, Lin Juan, Wang Lijin and Zhang Hui. 2017. "Hybrid discrete artificial bee colony algorithm with threshold acceptance criterion for traveling salesman problem." Information Sciences, vol.421, 70--84.
[17]
Petr Stodola, Pavel Otřísal and Kamila Hasilová. 2022. "Adaptive ant colony optimization with node clustering applied to the travelling salesman problem." Swarm and Evolutionary Computation, vol.70, 101056.
[18]
Emile Aarts, Emile HL Aarts, and Jan Karel Lenstra. 2003. "Local search in combinatorial optimization." Princeton University Press.
[19]
Jean-Claude Thill and Yu-Cheng Kuo. 2018. "The Nearest Neighbor Ant Colony System: A Spatially-Explicit Algorithm for the Traveling Salesman Problem." Spatial analysis and location modeling in urban and regional systems, 301--322.
[20]
C. Nilsson. 2003. "Heuristics for the traveling salesman problem." Linkoping University, 38, 00085-9.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation
July 2023
2519 pages
ISBN:9798400701207
DOI:10.1145/3583133
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 July 2023

Check for updates

Author Tags

  1. ant colony optimization
  2. traveling salesman problem
  3. outlier
  4. route construction

Qualifiers

  • Poster

Conference

GECCO '23 Companion
Sponsor:

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 46
    Total Downloads
  • Downloads (Last 12 months)11
  • Downloads (Last 6 weeks)0
Reflects downloads up to 30 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media