Abstract
This paper presents a massively parallel evolutionary algorithm with local search mechanism dedicated to dynamic optimization. Its application for solving Dynamic Traveling Salesman Problem (DTSP) is discussed. The algorithm is designed for many-core graphics processors with the Compute Unified Device Architecture (CUDA), which is a parallel computing architecture for nVidia graphics processors. Experiments on a number of benchmark DTSP problems confirmed the efficiency of the algorithm and the parallel computing model designed. © 2012 Springer-Verlag.
Cite
CITATION STYLE
Filipiak, P., & Lipiński, P. (2012). Parallel CHC algorithm for solving dynamic traveling salesman problem using many-core GPU. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7557 LNAI, pp. 305–314). https://doi.org/10.1007/978-3-642-33185-5_34
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