Research On The Modeling And Control Ctrategy Of Urban Sanitation Vehicle Scheduling System

With the development of urbanization and industrialization,the amount of municipal solid waste keeps growing in China.The existing garbage cleaning modes have disadvantages,such as low efficiency,poor real-time performance,difficult management,low degree of resource recycling and the single treatment method.Based on these,the strategy of constructing sanitation vehicle dispatch system under the mixed recovery and centralized sorting model are proposed.The current situation of waste generation,collection and transportation in sanitation vehicles,and elaborated the significance and content of this study are firstly introduced.The next is the related theories of the urban sanitation vehicle dispatching system,which mainly includes the theoretical basis for the collection and transportation mode,the site selection optimization and transport route optimization.Through the research and data review,the dynamic probabilistic model for garbage meta-data generation is proposed,which lays a theoretical foundation for mathematical modeling of this dissertation.The system of collecting and transporting sanitation vehicles with sorting centers is put forward.Through the center,the garbage is sorted and recycled.Because the transportation system of sanitation vehicles involves the problem of facility location and sanitation vehicle route optimization,the mathematical models of the two problems are combined,abstracts the various assumptions into mathematical constraints.A hybrid algorithm using genetic algorithm and tuba search algorithm is adopted.Solve the problem of facility location and sanitation vehicle route planning,finally form a mathematical model of the urban sanitation vehicle dispatch system.An example to test the model and algorithm is selected in the dissertation.The test results show the reliability of the model and the superiority of the algorithm.Then analyzing the cost of the model and the sensitivity of the algorithm parameters,the results show the collection and transportation cost has a greater impact on the total,and the change in the algorithm parameters will not have a great impact on the total cost,indicating that the algorithm has strong robustness to the parameter changes.