An Improved Fuzzy Based Glowworm Algorithm

نویسندگان

  • Behnam Iranpour
  • Mohammadreza Meybodi
چکیده

Glowworm swarm optimization algorithm is one of the most novel algorithms based on swarm intelligence and inspired from light emission behavior of glowworms to attract a peer or prey in nature. The main application of this algorithm is to occupy all local optima of multi modal functions. This algorithm has shown some such weaknesses in global search as low convergence rate, not so much accuracy in computations and time consuming computations. In this paper, an innovative glowworm algorithm via fuzzy logic concepts is represented which removes disadvantages of all standard glowworm algorithms to a high extent. Experimental results of well known benchmark functions show a proper efficiency of the proposed algorithm in contrast to other similar algorithms.

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تاریخ انتشار 2012