A multi-population based parallel genetic algorithm for multiprocessor task scheduling with Communication Costs

@article{Morady2016AMB,
  title={A multi-population based parallel genetic algorithm for multiprocessor task scheduling with Communication Costs},
  author={Rashid Morady and Deniz Dal},
  journal={2016 IEEE Symposium on Computers and Communication (ISCC)},
  year={2016},
  pages={766-772}
}
Multiprocessor task scheduling is one of the hardest combinatorial optimization problems in parallel and distributed systems. It is known as NP-hard and therefore, scanning the whole search space using an exact algorithm to find the optimal solution is not practical. Instead, metaheuristics are mostly employed to find a near-optimal solution in a reasonable amount of time. In this paper, a multi-population based parallel genetic algorithm is presented for the optimization of multiprocessor task… CONTINUE READING
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Showing 1-10 of 19 references

Comparison of Bounded Number of Processors (BNP) Class of Scheduling Algorithms Based on Matrices

  • R. Rajak
  • GESJ: Computer Science and Telecommunications,
  • 2012
1 Excerpt

Task Graph Scheduling on Multiprocessor System Using Genetic Algorithm

  • A. Bansal, R. Kaur
  • IJERT: International Journal of Engineering…
  • 2012
2 Excerpts

Arzil, “A Hybrid Method for Task Scheduling”, in ICETC'10

  • H. M. Ghader, S.A.K. Fakhr
  • Proceedings of the 2nd International Conference…
  • 2010
1 Excerpt

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