Multi-Objective Hybrid Evolutionary Optimization with Automatic Switching

In this work, a multi-objective hybrid optimizer is presented. The optimizer uses several multi-objective evolutionary optimization algorithms and orchestrates the application of these algorithms to multi-objective optimization problems, using an automatic internal switching algorithm. The switching algorithm is designed to favor those search algorithms that quickly improve the Pareto approximation and grades improvements using five criteria. A thorough testing of the reliability and accuracy of the multi-objective hybrid optimizer against a number of prominent multi-objective optimization algorithms and one hybrid optimizer confirmed that multi-objective hybrid optimizer performs reliably and accurately. I