Mosquito flying optimization (MFO)

This is a new optimization algorithm which mimic the behavior of mosquito to find a hole in mosquito net, if any. Both the flying and sliding motion of the mosquito have been modelled and incorporated in the algorithm. The algorithm was tested for global minima on different type of benchmark functions of various dimension and modality. Namely Gramacy & Lee, Ackley, Rastrigin, Rosenbrock, Griewank and Schwefel functions of one, two, five, ten and thirty dimensions. The experiment was done with thirty different seeds generated randomly for each function and dimension. The algorithm was found to be efficient, convergent and accurate.