A new algorithm using Pareto Archive Evolution Strategy to Multi-objective optimization problem

Many multi-objective optimization algorithms combine with different objectives into one objective using weighting method. In this paper, a novel method named Pareto Archive Evolution Strategy (PAES) which only makes one mutation to create one new solution and use an "archive" which are called Non-Dominated Archive to store the best solution, is introduced. This procedure is completed by a special approach-adaptive grid method, which decides what and which solution are to be archived and where the grid location the solution would be stored. The Pareto front is to be found by this procedure quicker than the classical Multi-objective Genetic Algorithm (MOGA). Simulation results show that the PAES is effective to the multi-objective optimization problems and have the better performance on the time complexity.