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Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

S. V. Ghorpade, S. M. Kamalapur
Department of Computer Engineering, KKWIEER, University of Pune, India
International Journal of Computer Science and Mobile Computing, Vol.3, Issue.7, pg. 268-274, 2014

@article{ghorpade2014solution,

   title={Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU},

   author={Ghorpade, Mr SV and Kamalapur, Mrs SM},

   year={2014}

}

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Local search metaheuristic algorithms are proven & powerful combinatorial optimization strategies to tackle hard problems like traveling salesman problem. These algorithms explore & evaluate neighbors of a single solution. Time Consuming LSM algorithms can be improved by parallelizing exploration & evaluation of neighbors of a solution. GPU architecture is suitable for algorithms of single program multiple data parallelism. Implemented algorithm reduces time consuming memory transfers and improves computational time by efficient use of memory hierarchy.
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