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Volume 54 Issue 2
Jun.  2019
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Article Contents
Journal of Southwest Jiaotong University  > 2019  >  54(2): 428-435.
WU Guanfeng, XU Yang, CHANG Wenjing, CHEN Shuwei, XU Peng. Parallel Genetic Algorithm for SAT Problems Based on OpenMP[J]. Journal of Southwest Jiaotong University, 2019, 54(2): 428-435. doi: 10.3969/j.issn.0258-2724.20170700
Citation: WU Guanfeng, XU Yang, CHANG Wenjing, CHEN Shuwei, XU Peng. Parallel Genetic Algorithm for SAT Problems Based on OpenMP[J]. Journal of Southwest Jiaotong University, 2019, 54(2): 428-435. doi: 10.3969/j.issn.0258-2724.20170700
shu

Parallel Genetic Algorithm for SAT Problems Based on OpenMP

doi: 10.3969/j.issn.0258-2724.20170700
  • Received Date: 20 Sep 2017
  • Rev Recd Date: 04 Apr 2018
    • Available Online: 30 May 2018
  • Publish Date: 01 Apr 2019
    Abstract
  • To improve solving efficiency for SAT (boolean satisfiability) problems, a combination of genetic algorithm (GA) with local search algorithm (LSA) on the OpenMP (open multi-processing) framework was proposed. This combination improved the selection algorithm in the hybrid genetic algorithm (HGA) and reduced the time complexity of the original selection operation to O(N). The compiler guide statement #pragma omp parallel in OpenMP was applied to coarse-grained parallelization driven HGA, and the #pragma omp single statement block was used to implement the synchronization migration operation of the individuals in different sub-groups. Compared with the similar algorithm, HCGA (hybrid cloud genetic algorithm), both the improved algorithm (HGA) and the coarse-grained parallel hybrid genetic algorithm (CGPHGA) significantly improved solution success rate and problem solving efficiency. Solution success rate for some problems was increased by 5 times.

     

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