Abstract
Hybrid metaheuristics are powerful methods for solving complex problems in science and industry. Nevertheless, the resolution time remains prohibitive when dealing with large problem instances. As a result, the use of GPU computing has been recognized as a major way to speed up the search process. However, most GPU-accelerated algorithms of the literature do not take benefits of all the available CPU cores. In this paper, we introduce a new guideline for the design and implementation of effective hybrid metaheuristics using heterogeneous resources. © 2012 Springer-Verlag.
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CITATION STYLE
Van Luong, T., Taillard, E., Melab, N., & Talbi, E. G. (2012). Parallelization strategies for hybrid metaheuristics using a single GPU and multi-core resources. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7492 LNCS, pp. 368–377). https://doi.org/10.1007/978-3-642-32964-7_37
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