Multi-objective optimization genetic algorithm keeping diversity of population

A multi-objective genetic algorithm keeping diversity of the population is proposed.The algorithm uses a metric based on entropy to measure the diversity of the population in the case of multi-objective space.The evolving state of the current population is associated with the running mechanism of the algorithm by the diversity metric,and several strategies are designed to enhance the extent of exploration of the algorithm,which widens the searching range of the algorithm,and increases the diversity of the evolving population and prevents premature convergence.The computational complexity of the algorithm is analyzed theoretically.Simulation results indicate that the proposed algorithm has good performance of convergence and distribution.