The Multi-objective Dynamic Stochastic Optimization Models Of China's Industrial Structure

China has made a tremendous achievement on economy since the reform and opening, the Gross of National Product has been growing, and the people's standard of living has been markedly improving. Optimization of the industrial structure aiming at economic growth enable the economic resources flowing from the low relatively productivity to high relatively productivity of industries, and which will also drives the total economy efficiency growing, and promotes the national economy. However, in recent years, at the same time of rapidly growing in economy, the conflict between economy growing with energy consumption and environmental pollution has been become increasingly vigorous, and therefore energy-saving and emission-reducing have been become a strategy target in China's "11th Five-Year" plan. As thus, the study up on multi-objective optimization of China's industrial structure has been with important theoretical and practical significance.Firstly, this paper analyzes the factors influencing the changing in the industrial structure, sums up the industry linkage of changing trends by research on the industry linkage under the economic growth perspective, and defines which industries and what demands will effectively stimulate economic growth, thus there has a basic understanding about optimization of China's industrial structure. Secondly, the author demonstrates the relationship between the industrial structure changing with economic fluctuations, energy consumption and pollution control by using empirical research and theoretical analysis. This paper points out that except the economic growth target, the energy consumption and pollution control can also be used as objectives by optimization of the industrial structure. In constructing the model of the optimization of the industrial structure, the pollutant emission will be a stochastic variable, by using stochastic optimization it will solve the uncertainty problems in environmental pollution, on this basis, the author constructed a China's industrial multi-objective dynamic Stochastic optimization model, and has given model solving methods.In the dynamic optimization empirical study, this paper revising direct consumption coefficient matrix and calculating investment coefficient matrix solves the data problem in empirical study. The results of the optimization model show that if under a single economic growth target, from 2005 to 2020 the China's average annual economy growth rate could achieve about 12 percent, but which would have to cost enormous energy consumption and environmental pollution. And if under single energy consumption targets or pollution control targets, although the energy consumption could be achieved with the effective control of emissions, but the rate of economy growth would be lower. In the multi-objective optimization model, it will be realized that the energy consumption and pollution emissions could meet the objectives and the requirements in "11th Five-Year" plan, furthermore the economy would maintaining a relatively high growth rate, the annual growth rate could achieve 9 to 10 percent, so the results of the optimization model are approved. Finally, based on the empirical research findings the author put forward some recommendations on policy of the corresponding optimization of China's industrial.