Research On The Network Design Of End Of Life Automobile Reverse Logistics

Since 2009, China has been the first place of automobile in both production and marketing. While enjoying economic growth and achievement of automobile industry development, a fact that growth of production and marketing will certainly raise the quantity of end of life automotive (EOLA) should be considered. If the EOLA is misdealt, the problems of resource, environment, economics and society will appear. On the contrary, if reverse logistics (RL) network is designed reasonably and this problem of EOLA is handled well, resources will be saved, pollution of the environment will be reduced and economic returns will be improved. The most important it will be beneficial to social harmony and sustainable development.As the foundation and core of the RL, whether it is reasonable determine the performance of RL. After literature research, a phenomenon is found, RL especially network design has been discussed adequately, but research on automobile industry RL is not enough. This is out of all relation to the development of automobile industry. In view of this, in order to make network design more scientific, EOLA RL network design is been researched. More details as follows:First of all, a multilevel RL network including client areas, recycling points, dismantling points, reproducing points and landfill is considered. A MILP model whose objective function is minimum cost is proposed to optimize network design. After doing this, a plan including site location and flow distribution will be obtained.Secondly, the quantity of EOLA is an important index that determines the scale of the RL network and it is also a crucial parameter of the MILP model. In consideration of this, a model of forecasting the quantity of EOLA is introduced in Chapter 5. This model that based on principal component analysis (PCA) and back propagation (BP) neural networks provides parameter for the demonstration of Shanghai in Chapter 6.Thirdly, on the basis of Shanghai existing RL network, forecasted and collected parameters are applied to the MILP model to replan and redesign. The demonstration of Shanghai indicates the effectiveness of MILP model and PCA-BP model.