SINGLE-WALK PARALLELIZATION OF THE GENETIC ALGORITHM

Wojciech Bożejko, Mieczyslaw Wodecki

2011

Abstract

This paper aims at presenting theoretical properties which can be used to approximate the theoretical speedup of parallel genetic algorithms. The most frequently parallelization method employed to genetic algorithm implements a master-slave model by distributing the most computationally exhausting elements of the algorithm (usually evaluation of the fitness function, i.e. cost function calculation) among a number of processors (slaves). This master-slave parallelization is regarded as easy in programming, which makes it popular with practitioners. Additionally, if the master processor keeps the population (and slave processors are used only as computational units for individuals fitness function evaluation), it explores the solution space in exactly the same manner as the sequential genetic algorithm. In this case we can say that we analyze the single-walk parallel genetic algorithm.

References

  1. Boz?ejko, W., Pempera, J., and Smutnicki, C. (2008a). Multi-thread parallel metaheuristics for the flow shop problem. In Artificial Intelligence and Soft Computing (eds. L. Rutkowski, R. Tadeusiewicz, L.A. Zadeh, J.M. Zurada), pages 454-462. IEEE Computational Intelligence Society - Poland Chapter and the Polish Neural Network Society.
  2. Boz?ejko, W., Pempera, J., and Smutnicki, C. (2008b). Parallel single-thread strategies in scheduling. In Artificial Intelligence and Soft Computing, volume 5097 of Lecture Notes in Artificial Intelligence, pages 995-1006. Springer.
  3. Boz?ejko, W., UchroÁski, M., and aw Wodecki, M. (2010). Parallel hybrid metaheuristics for the flexible job shop problem. Computers & Industrial Engineering, 59:323-333.
  4. Boz?ejko, W. and Wodecki, M. (2006). A new inter-island genetic operator for optimization problems with block properties. volume 4029 of Lecture Notes in Artificial Intelligence, pages 324-333. Springer.
  5. Cahon, S., Melab, N., and Talbi, E.-G. (2004). Paradiseo on condor-mw for optimization on computational grids. http://www.lifl.fr/ cahon/cmw/index.html.
  6. Cant ú-Paz, E. (2005). Theory of parallel genetic algorithms. In Alba, E., editor, Parallel Metaheuristics, pages 425-444. Wiley.
  7. Czech, Z. (2002). Three parallel algorithms for simulated annealing. volume 2328 of Lecture Notes in Artificial Intelligence, pages 210-217. Springer.
  8. Davidor, Y. (1991). A naturally occuring niche and species phenomenon: The model and first results. In Proceedings of the Fourth Internatinal Conference of Genetic Algorithms, pages 257-263.
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Paper Citation


in Harvard Style

Bożejko W. and Wodecki M. (2011). SINGLE-WALK PARALLELIZATION OF THE GENETIC ALGORITHM . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 586-590. DOI: 10.5220/0003177805860590


in Bibtex Style

@conference{icaart11,
author={Wojciech Bożejko and Mieczyslaw Wodecki},
title={SINGLE-WALK PARALLELIZATION OF THE GENETIC ALGORITHM},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={586-590},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003177805860590},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - SINGLE-WALK PARALLELIZATION OF THE GENETIC ALGORITHM
SN - 978-989-8425-40-9
AU - Bożejko W.
AU - Wodecki M.
PY - 2011
SP - 586
EP - 590
DO - 10.5220/0003177805860590