Abstract
A hybrid genetic algorithm for global multi-objective optimization is parallelized and applied to solve competitive facility location problems. The impact of usage of the local search on the performance of the parallel algorithm has been investigated. An asynchronous version of the parallel genetic algorithm with the local search has been proposed and investigated by solving competitive facility location problem utilizing hybrid distributed and shared memory parallel programming model on high performance computing system. © 2014 Springer-Verlag.
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CITATION STYLE
Lančinskas, A., & Žilinskas, J. (2014). Parallel multi-objective memetic algorithm for competitive facility location. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8385 LNCS, pp. 354–363). Springer Verlag. https://doi.org/10.1007/978-3-642-55195-6_33
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