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National Repository of Grey Literature 1 records found  Search took 0.01 seconds. 
Acceleration of Discrete Optimization Heuristics Using GPU
 Pecháček, Václav ; Jaroš, Jiří (referee) ; Pospíchal, Petr (advisor)
Thesis deals with discrete optimization problems. It focusses on faster ways to find good solutions by means of heuristics and parallel processing. Based on ant colony optimization (ACO) algorithm coupled with k-optimization local search approach, it aims at massively parallel computing on graphics processors provided by Nvidia CUDA platform. Well-known travelling salesman problem (TSP) is used as a case study. Solution is based on dividing task into subproblems using tour-based partitioning, parallel processing of distinct parts and their consecutive recombination. Provided parallel code can perform computation more than seventeen times faster than the sequential version.
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