MOX: A novel global optimization algorithm inspired from Oviposition site selection and egg hatching inhibition in mosquitoes

In this paper, we describe a novel computational intelligence approach to numerical optimization for finding the global optima of a multidimensional function based upon biological inspirations drawn from the highly selective behavior of female mosquitoes in choosing a habitat to lay their eggs and the inhibition of those eggs to hatch into the next stage.1 Results of the proposed approach over a number of benchmark problems are also presented. Comparison of those results with existing methods in the literature clearly indicates the efficacy of the proposed scheme in maintaining a high success rate while reducing the number of function evaluations required to reach a goal value for an optimization problem.