The Study Of Recycling System Of Waste Household Appliances And Route Optimization Methods

In recent years, China has entered the peak of obsolescence of waste householdappliances again with the speed of the upgrade accelerated gradually and product lifecycle shorter increasingly. In general waste household appliances contain a largeamount of metal materials. Collecting the waste appliances properly can not onlyachieve the reuse of resource and bring economic benefits for enterprises, but also it canachieve the goal of environmental and ecological protection. The recycling of wastehousehold appliances in reverse logistics will become a new area of development ofChina’s logistics in the future.In this paper, reverse logistics of waste household appliances is the research object,which contains the construction of recycling system and the study of vehicle routingoptimization. This paper mainly includes the following aspects:(1)The theories of reverse logistics, reverse logistics of waste household areintroduced. At the same time, it points out the mode of operation and the obstacles tothe development of reverse logistics of waste household appliances.(2)The paper constructs a waste household appliances network informationplatform for recycling. The platform updates in real time information of recovery,strengthens communication and contact with the recycling center and collection points.As a result,it reduces the dispersion, diversity and uncertainty of reverse logistics. Weachieve full recovery and utilization of waste household appliances and the protectionof the ecological environment with the help of recycling system of waste householdappliances with a closed loop.(3)We establish a model of vehicle routing optimization of waste householdappliances based on cost. The model is a definite model. It is a model, which it studiesthe known location of recovery customer, definite recycling amounts and the recyclingcenter which meets some constraint conditions, assigning vehicles for recycling and toconfirming each vehicles driving route, in order to complete the task allthe recovery, and the minimum operation cost. We apply the ant colony algorithm tosolve the model. As the convergence speed of the ant colony algorithm is slow and it iseasy to fall into local optimal solution, we improve the algorithm. Finally, this paperverifies the validity of the algorithm by an specific example.