Study And Application Of Intelligent Evolution Optimization Algorithm

Global optimization is a research focus in the fields of science and engineering. It's difficult for the conventional methods such as Newton descending method and grads method to find global optimal solution. Differential evolution algorithm.is widely used because of its good convergence, brief model, easy implementation and less control parameters. Multi-objective optimization become a research focus with industrial development and also a difficult point, non-dominated sorting genetic algorithm(NSGA) shows great advantages in the problems of multi-objective optimization, but its disadvantages are discovered when it is deeply studied and widely used. To solve the problems of multi-objective optimization more effectively, the modified non-dominated sorting genetic algorithm (NSGA-II) is proposed by Deb and others on the basis of NSGA. In this paper, the basic theories and processes of these two kinds of intelligent evolution optimization algorithms are systematically introduced and applied them to the sintering burdening optimization.The main contents are as follows:(1) The problems of global optimization and the current state of the research on these problems are introduced. Meanwhile, the basic theories of DE and NSGA are also systematically presented. In addition, modified DE and NSGA-II are introduced.(2) Basic concepts and research meaning of sintering burdening are introduced, the basic theories of differential evolution are studied and modify its limitation. We use differential evolution to optimize sintering burdening because of its advantages on solving problems of global optimization. The material costs are set as the objective of optimization model, restrictions are: chemical components, sintering alkalinity, non-negative restricts of material dosage and restricts of all material gross. The simulation shows the feasibility of differential evolution on sintering burdening optimization. Compared with other algorithm differential evolution is very useful because of its easy implementation and less control parameter, so it is a new method for sintering burdening optimization.(3) Based on the NSGA-II theory, the novel approach of sintering burdening optimization taking properties into account is proposed. Reductive performance and mechanical tolerance, using coefficient are set as the objectives of optimization model. Using NSGA-II to optimize this question, the result shows NSGA-II is very useful in solving multi-objective questions, so an efficient method of sintering burdening optimization considering properties is proposed.