Improved Multi-objective Genetic Algorithm Based on Parallel Hybrid Evolutionary Theory
Yingyong Zou, Yongde Zhang · International Journal of Hybrid Information Technology · 2015
Based on the analysis on the basic principles and characteristics of the existing multiobjective genetic algorithm (MOGA), an improved multi-objective GA with elites maintain is put forward based on non-dominated sorting genetic algorithm (NSGA).NSGA-II algorithm theory and parallel hybrid evolutionary theory is described in detail.The design principle, process and detailed implementations of the improved MOGA are given.IMNSGA-II algorithm and NSGA-II algorithm are applied to test the performance of the two algorithms for different test function, experiments of example are preformed.Experimental results show that the improved MOGA achieved the optimal between the convergence and diversity.