Abstract
The traveling salesman problem (TSP) is probably the most widely studied combinatorial optimization problem and has become a standard testbed for new algorithmic ideas. Recently the use of a GPU (Graphics Processing Unit) to accelerate non-graphics computations has attracted much attention due to its high performance and low cost. This paper presents a novel method to solve TSP with a GPU based on the CUDA architecture. The proposed method highly parallelizes a serial metaheuristic algorithm which is a genetic algorithm with the OX (order crossover) operator and the 2-opt local search. The experiments with an NVIDIA GeForce GTX285 GPU and a single core of 3.0 GHz Intel Core2 Duo E6850 CPU show that our GPU implementation is about up to 24.2 times faster than the corresponding CPU implementation.
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Fujimoto, N., Tsutsui, S. (2011). A Highly-Parallel TSP Solver for a GPU Computing Platform. In: Dimov, I., Dimova, S., Kolkovska, N. (eds) Numerical Methods and Applications. NMA 2010. Lecture Notes in Computer Science, vol 6046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18466-6_31
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DOI: https://doi.org/10.1007/978-3-642-18466-6_31
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