Multi-objective hybrid, evolutionary optimization with automatic switching among constituent algorithms

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.