Grey Wolves Attack Process for the Pareto Optimal Front Construction in the Multiobjective Optimization

We propose a new metaheuristic, HmGWOGA-MO, for solving multiobjective optimization problems operating with population of solutions. The method is hybridization the HmGWOGA method, which single objective and ϵ-constraint approach, an aggregation technique. technique one best ways to transform problem many functions into because it works even if has any kind Pareto optimal front. Previously, was designed optimize positive single-objective function without constraints. obtained solutions are good. That why, in this current work, we combined have approach resolution problems. Our proceeds by transforming given constraints unconstrained function. With five different test varying fronts been successfully solved, results compared those NSGA-II regarding convergence towards front distribution on This numerical study indicates that HmGWOGA-MO choice when most important performance parameter.