A New MGlaber Approach as an Example of Novel Artificial Acari Optimization

The proposed MGlaber method is based on observation of the behavior of mites called Macrocheles glaber (Muller, 1860). It opens the series of optimization methods inspired by the behavior of mites, which we have given a common name: Artificial Acari Optimization. Acarologists observed three stages the ovoviviparity process consists of, i.e.: preoviposition behaviour, oviposition behaviour (which is followed by holding an egg below the gnathosoma) and hatching of the larva supported by the female. It seems that the ovoviviparity phenomenon in this species is favoured by two factors, i.e.: poor feeding and poor quality of substrate. Experimental tests on a genetic algorithm were carried out. The MGlaber method was worked into a genetic algorithm by replacing crossig and mutation methods. The obtained results indicate to significant increase in the algorithm convergence without side-effects in the form of stopping of evolution at local extremes. The experiment was carried out one hundred times on random starting populations. No significant deviations of the measured results were observed. The research demonstrated significant increase in the algorithm operation speed. Convergence of evolution has increased about ten times. It should be noted here that MGlaber method was not only or even not primarily created for genetic algorithms. The authors perceive large potential for its application in all optimization methods where the decision about further future of the solutions is taken as a result of the evaluation of the objective function value. Therefore the authors treat this paper as the beginning of a cycle on Artificial Acari Optimization, which will include a series of methods inspired by behaviour of different species of mites.