Extension and performance evaluation of recent optimization techniques on mixed integer optimization problems

In this work, we extend three recently developed computational intelligence techniques, viz., Ying-Yang Pair Optimization, Moth-flame Optimization, and Grey Wolf Optimization for real variable optimization problems to solve mixed integer optimization problems. As these techniques are developed primarily for continuous variables, three strategies to handle the integer variables are considered in this article thereby leading to 9 variants. These variants are evaluated on ten unique runs of eighteen mixed integer constrained optimization problems and their performance is evaluated under equal functional evaluations.