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. Improved Ant Colony Optimization with Local Search for Traveling Salesman Problem
Loading...
Thumbnail Image

Improved Ant Colony Optimization with Local Search for Traveling Salesman Problem

Author(s)
Thammano, Arit
Oonsrikaw, Yindee
Date Issued
July 1, 2019
Type
Conference Paper
DOI
10.1109/SNPD.2019.8935817
Abstract
Improved Ant Colony Optimization (IACO) with a local search algorithm is proposed for better finding near optimal solution of Traveling Salesman Problem (TSP). In this work, IACO was combined with each of four local search operators in order to enhance IACO exploration capacity. The performances of IACO and the four local search were comparatively tested on a set of benchmark symmetric TSP instances. The experimental results show that IACO.
Citation
Proceedings 20th IEEE Acis International Conference on Software Engineering Artificial Intelligence Networking and Parallel Distributed Computing Snpd 2019, 22-27, 2019
Subjects

2-opt

3-opt

ant colony

simulated annealing

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