A critical analysis of parameter adaptation in ant colony optimization
type: Dataset
description: Applying parameter adaptation means operating on parameters of an algorithm while it is tackling an instance. For ant colony optimization, several parameter adaptation methods have been proposed. In the literature, these methods have been shown to improve the quality of the results achieved in some particular contexts. In particular, they proved to be successful when applied to novel ant colony optimization algorithms for tackling problems that are not a classical testbed for optimization algorithms. In this paper, we show that the adaptation methods proposed so far do not improve, and often even worsen the performance when applied to high performing ant colony optimization algorithms for some classical combinatorial optimization problems.
issued: 2026-05-09T07:57:48.692076
language: en
modified: 2026-05-09T07:57:48.692080
contact point: Organization
  fn: CCSD
keyword: algorithme
keyword: infoeu-reposemanticsarticle
keyword: intelligence-artificielle
keyword: journal-articles
keyword: optimisation
keyword: sccocompcognitive-sciencecomputer-science
landing page: 1935-3812

A critical analysis of parameter adaptation in ant colony optimization
type: Distribution
format: HTML
issued: 2026-05-09T07:57:48.693844
modified: 2026-05-09T07:57:48.685275
access URL: https://hal.science/hal-00874517

test_moissonnage_selune
type: Agent