Improved strategies and researches of NSGA-II algorithm

Non-dominated Sorting Genetic Algorithm with elitism(NSGA-Ⅱ) is widely used in multi-objective optimization fields.Uneven distribution of population convergence,poor performance in global search and low running efficiency of this algorithm are analyzed in this paper.Four improved strategies are proposed according to these limitations:improved sorting strategy,arithmetic cross operator strategy,sorting rank according to the demand strategy and selecting strategy with the given threshold.The simulations prove that the non-dominated Pareto optimal solutions have better distribution and faster convergence at the same time in typical functions.