Research On Layout Of Reverse Logistics Network For Express Packaging Recovery

In recent years, with the rapid growth of the electronic business, the express industry has achieved rapid development in our country. In China, the delivery quantity of express was 14 billion in 2014, up 52% from a year earlier, and had become the world’first. However, the express industry also produces a large number of packaging waste, which will causes environmental pollution and resource waste problem. Fortunately, more and more social public have realized the seriousness of the problem, and try to recycle the express packaging waste, but still exist a lot of difficulties in the process of the express packaging recycling, such as the lack of recycling channels, no unified standard packing and reused packaging easily damaged. All these problems need to be addressed.Therefore, the paper firstly analyzes the current recycling situation of express packaging in our country. Then based on experienced management experience of foreign reverse logistics network, the paper puts forward to build a express packaging recycling system, and designs the recycling process, the packaging standardization and the recycling incentives. Secondly, according to the express packaging recycling system, the paper carries on the optimization of reverse logistics network. The key of the reverse logistics network optimization is to solve the facility location, transportation route scheduling and inventory control problem, and there is close connection between this three problems. Therefore, the paper establishes the integrated optimization model to solve the Location-Routing-the Inventory Problem (LRIP), in order to minimize the cost of the express packaging recycling system. Because the LRIP problem belongs to NP-Hard problem, the two-phase heuristic algorithm is designed to solve the model. Finally, the paper choses an express enterprise in Dalian as an example, and collect the recycling data to calculate the model.The results also show that the design of the model and the algorithm is feasible and effective.