A New Hybrid Approach for Nonlinear Mini-max Problems

For a class of nonlinear min-max problems,because aggregate function method is simple and easy to implement,it has always been more popular smooth processing technology,However,it is not easy to choose a suitable penalty factor.By employing the feasibility-based rule,this paper proposes the hybrid Hook-jeveese search method and particle swarm optimization with a feasibility-based rule for nonlinear min-max problems.Compared with the aggregate function,feasible basis rule does not require additional parameters,and it dictates particles to the feasible domain fly quickly.Simulation and comparisons based on two well-known problems demonstrate the effectiveness,efficiency and robustness on initial populations of the proposed method.Moreover,the new method obtains some solutions better than those previously reported in the literature.