![Sample our Physical Sciences journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/110819/TOC-Subject-Sample-2021-Physical-Sciences.jpg"})
Abstract
The multi-objective optimization NSGA-II approach has been proved that, in most of times, it has much better spread of solutions and better convergence near the true Pareto-optimal than mostly Pareto-optimal method. But there are also disadvantages to restrict the spread uniformity in some problems. This paper overcomes these disadvantages to get three modifications such as the cumulate dummy fitness strategy, disconnected filling strategy, and throwing off strategy by selection limit. The comparison with simple NSGA-II shows that the great efficiency is achieved by using the improved NSGA-II in most of times, because the improved approach can spread value space and give a more reasonable rule for preponderant individuals.