A very optimistic method of minimization (VOMMI) for unconstrained problems

Numerous nontraditional optimization techniques have been suggested in literature to solve highly complicated multimodal mathematical functions. The complexity involved in solving the functions increases with the increase in the number as well as the range of the variables. Most of the optimization algorithms involve much complexity in their understanding and implementation and this complexity is found to be proportional to the number of algorithm specific parameters. Hence, there is a need to find simple but effective algorithms with minimum number of algorithm specific parameters. The present work aims to introduce a novel and simple methodology for optimization without sacrificing the effectiveness. It relies on following the 'existing best practices' to achieve improvement. The algorithm employs two factors represented as luck and effort factors and solves many complex unconstrained optimization problems effectively. The proposed algorithm is found to be successful in providing better solutions than some popular algorithms for certain complicated problems, reported in literature.