Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Conference paper
Title: Parameterized complexity analysis and more effective construction methods for ACO algorithms and the Euclidean traveling salesperson problem
Author: Nallaperuma, S.
Sutton, A.
Neumann, F.
Citation: 2013 IEEE Congress on Evolutionary Computation (CEC): pp.2045-2052
Publisher: IEEE
Publisher Place: United States
Issue Date: 2013
ISBN: 9781479904525
Conference Name: IEEE Congress on Evolutionary Computation (2013 : Cancun, Mexico)
Statement of
Samadhi Nallaperuma, Andrew M. Sutton, Frank Neumann
Abstract: We propose a new construction procedure for ant colony optimization (ACO) algorithms working on the Euclidean traveling salesperson problem (TSP) that preserves the ordering on the convex hull of the points in the instance. The procedure is inspired by theoretical analyses for simple evolutionary algorithms that are provably more efficient on instances where the number of inner points of the instance is not too large. We integrate the construction procedure into the well-known MaxMin Ant System (MMAS) and empirically show that it leads to more efficient optimization on instances where the number of inner points is not too high.
Rights: ©2013 IEEE
DOI: 10.1109/CEC.2013.6557810
Published version:
Appears in Collections:Aurora harvest
Computer Science publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.