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GECCO
2005
Springer

Solving large scale combinatorial optimization using PMA-SLS

8 years 11 months ago
Solving large scale combinatorial optimization using PMA-SLS
Memetic algorithms have become to gain increasingly important for solving large scale combinatorial optimization problems. Typically, the extent of the application of local searches in canonical memetic algorithm is based on the principle of “more is better”. In the same spirit, the island model parallel memetic algorithm (PMA) is an important extension of the canonical memetic algorithm which applies local searches to every transitional solutions being considered. For PMA which applies complete local search, we termed it as PMA-CLS. In this paper, we consider the island model PMA with selective application of local search (PMA-SLS) and demonstrate its utility in solving complex combinatorial optimization problems, in particular largescale quadratic assignment problems (QAPs). Based on our empirical results, the PMA-SLS compared to the PMA-CLS, can reduce the computational time spent significantly with little or no lost of solution quality. This we concluded is due mainly to the a...
Jing Tang, Meng-Hiot Lim, Yew-Soon Ong, Meng Joo E
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Jing Tang, Meng-Hiot Lim, Yew-Soon Ong, Meng Joo Er
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