Paper Title:
Ant Colony Optimization with Local Search for Continuous Functions
  Abstract

Ant algorithms are a recently developed, population-based approach which was inspired by the observation of the behavior of ant colonies. Based on the ant colony optimization idea, we present a hybrid ant colony system (ACS) coupled with a pareto local search (PLS) algorithm, named PACS, and apply to the continuous functions optimization. The ACS makes firstly variable range into grid. In local search, we use the PLS to escape local optimum. Computational results for some benchmark problems demonstrate that the proposed approach has the high search superior solution ability.

  Info
Periodical
Advanced Materials Research (Volumes 204-210)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
1135-1138
DOI
10.4028/www.scientific.net/AMR.204-210.1135
Citation
C. M. Qi, "Ant Colony Optimization with Local Search for Continuous Functions", Advanced Materials Research, Vols. 204-210, pp. 1135-1138, 2011
Online since
February 2011
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Price
$32.00
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