The ACO Encoding

Moraglio, Alberto and Otero, Fernando E.B. and Johnson, Colin G. (2010) The ACO Encoding. In: Swarm Intelligence - 7th International Conference (ANTS 2010). (Full text available)

PDF - Author's Accepted Manuscript
Download (129kB) Preview
[img]
Preview
Official URL
http://www.cs.kent.ac.uk/pubs/2010/3176

Abstract

Ant Colony Optimization (ACO) differs substantially from other meta-heuristics such as Evolutionary Algorithms (EA). Two of its distinctive features are: (i) it is constructive rather than based on iterative improvements, and (ii) it employs problem knowledge in the construction process via the heuristic function, which is essential for its success. In this paper, we introduce the ACO encoding, which is a self-contained algorithmic component that can be readily used to make available these two particular features of ACO to any search algorithm for continuous spaces based on iterative improvements to solve combinatorial optimization problems.

Item Type: Conference or workshop item (UNSPECIFIED)
Uncontrolled keywords: determinacy analysis, Craig interpolants
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Depositing User: Fernando Otero
Date Deposited: 21 Sep 2012 09:49
Last Modified: 22 Feb 2016 10:18
Resource URI: https://kar.kent.ac.uk/id/eprint/30631 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year

Downloads

Downloads per month over past year