Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. Hybrid Ant Colony Optimization Method for the Traveling Salesman Problem
Loading...
Thumbnail Image

Hybrid Ant Colony Optimization Method for the Traveling Salesman Problem

Author(s)
Janjarassuk, Udom
Date Issued
January 1, 2024
Type
Conference Paper
DOI
10.1109/ICBIR61386.2024.10875933
Abstract
The traveling salesman problem (TSP) is a classic problem in computer science and operations research which involves finding the shortest possible route that visits a given set of cities. In this paper, we propose a hybrid algorithm for solving such problem. The algorithm combines the ant colony optimization (ACO) method with the 2-opt heuristic to improve the efficiency for solving the TSP. Instances from the TSPLIB were used to test the algorithm. The results showed that the hybrid ACO algorithm was more effective in solving the TSP as compared to the traditional ACO or the 2-opt heuristic methods.
Citation
Icbir 2024 2024 9th International Conference on Business and Industrial Research Proceedings, 292-295, 2024
Subjects

2-opt heuristic

algorithm

ant colony optimizati...

hybrid method

optimization

traveling salesman pr...

Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback