An Improved Nonlinear Multi-Objective Optimization Problem Based on Genetic Algorithm

Genetic algorithms for multi-objective optimization problem to be solved were studied. Through the elitist strategy analysis, it is an improved multi-objective optimization algorithm. The algorithm uses a data warehouse to store the optimal solution produced by individuals in each generation, from the way individuals adopt measures to phase out the individual data warehouse identical or similar, the algorithm also improved selection operator, so that the algorithm adaptive capacity enhancement, the new algorithm improves the algorithm performance, improves the quality of understanding between sets, can get a lot of optimal and balanced.