Discrete bee algorithms and their application in multivariable function optimization

  • Authors:

  • Mina Salim;M. T. Vakil-Baghmisheh

  • Affiliations:

  • ICT Research Center, Faculty of Electrical & Computer Engineering, University of Tabriz, Tabriz, Iran;ICT Research Center, Faculty of Electrical & Computer Engineering, University of Tabriz, Tabriz, Iran

  • Venue:
  • Artificial Intelligence Review
  • Year:
  • 2011

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Abstract

In this paper we present four discrete versions of two different existing honey bee optimization algorithms: the discrete artificial bee colony algorithm (DABC) and three versions of the discrete fast marriage in honey bee optimization algorithm (DFMBO1, DFMBO2, and DFMBO3). In these discretized algorithms we have utilized three logical operators, i.e. OR, AND and XOR operators. Then we have compared performances of our algorithms and those of three other bee algorithms, i.e. the artificial bee colony (ABC), the queen bee (QB), and the fast marriage in honey bee optimization (FMBO) on four benchmark functions for various numbers of variables up to 100. The obtained results show that our discrete algorithms are faster than other algorithms. In general, when precision of answer and number of variables are low, the difference between our new algorithms and the other three algorithms is small in terms of speed, but by increasing precision of answer and number of variables, the needed number of function evaluations for other algorithms increases beyond manageable amounts, hence their success rates decrease. Among our proposed discrete algorithms, the DFMBO3 is always fast, and achieves a success rate of 100% on all benchmarks with an average number of function evaluations not more than 1010.