The Hybrid Intelligent Optimization Algorithm and Multi-objective Optimization Based on Big Data

Multi objective optimization problem (MOP) usually has more than two objective functions, and the optimal solution based on Pareto frontier is obtained. The traditional optimization algorithm cannot meet the needs of industrial application when dealing with multi-objective optimization problems. With the good performance of evolutionary algorithm in solving complex problems, its application field is also extended to multi-objective optimization problems. The Pareto optimal solution and evaluation system of multi-objective optimization problem are analysed. Particle swarm optimization (PSO), one of the evolutionary algorithms based on swarm intelligence, is briefly introduced. The combination of particle swarm optimization algorithm and multi-objective optimization is studied.