DocumentCode :
2327500
Title :
A hybrid Memory-based ACO algorithm for the QAP
Author :
Leguizamón, Guillermo ; Arito, Franco ; Coello, Carlos A Coello
Author_Institution :
LIDIC, Univ. Nac. de San Luis, San Luis, Argentina
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
The performance of ant colony optimization (ACO) algorithms significantly improves when hybridized with local search procedures which strongly bias the search towards promising regions of the search space. In this work, we study a recently proposed Memory based ACO algorithm (MACO) which incorporates some tabu search principles into the solution construction process. This algorithm has also been hybridized with two local search procedures: 2-opt (M-ACO-2opt) and Tabu Search (M-ACO-TS). The performances of the two hybrid versions of M-ACO are analyzed on a set of instances of the Quadratic Assignment Problem (QAP). The results show that the hybrid versions of M-ACO are able to improve the quality of the best known solutions for several of the instances studied.
Keywords :
quadratic programming; search problems; QAP; ant colony optimization; hybrid memory based ACO algorithm; local search procedure; quadratic assignment problem; search space; tabu search; Algorithm design and analysis; Benchmark testing; Construction industry; Equations; Optimization; Probabilistic logic; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
Type :
conf
DOI :
10.1109/CEC.2010.5586132
Filename :
5586132
Link To Document :
بازگشت