Study On Evaluation And Optimization Of Muck Truck Transportation Route

With the constant development of domestic social economy,the number of new construction projects in various places is also increasing,followed by large-scale construction waste,and a large amount of construction waste brings many challenges to city managers,and while the muck truck transports construction waste between urban roads,it also brings a series of hidden safety problems.And most of the current research on this aspect is also It focuses on the management and control policies of construction waste and the development of on-board hardware equipment for muck trucks.However,as a key link in the whole process of construction waste management and control,the transport route lacks corresponding research on the rationality and applicability of its formulation.Therefore,this paper focuses on the transportation path of the muck truck,and conducts corresponding evaluation and optimization research from the aspects of cost and safety.In this paper,based on the road network data in the research area,the data of the transportation approval form and the track point data of the muck truck,the data is cleaned and other preprocessing operations are carried out.With the help of Arc GIS software and Baidu map API,the density analysis and analysis of the hot spot area of muck truck activity in the study area are carried out.The visual display of the transportation route provides the data basis for the route evaluation and route optimization in the following sections.Then,a hierarchical structure evaluation model is constructed from the cost and safety of construction waste transportation by combining the relative path length,the path average speed,the flow of muck vehicles,the road grade and the single and double lanes for the declared transportation route of the muck truck.The actual declared transportation route in the area is evaluated and analyzed,and the route with a lower evaluation score indicates that it has not passed the declaration.Then re-plan the routes that have not passed the declaration,that is,to provide a theoretical basis for the formulation of the transportation routes declared by the muck trucks of the transport unit,and build a dual-objective path optimization model suitable for the minimization of the transportation cost and transportation risk of the muck trucks.The time cost and fixed cost of transport units and road safety risks arising from transport will be considered simultaneously.Finally,in terms of solving the dual-objective path optimization model,this paper will solve the dual-objective problem by transforming the dual-objective into a single objective and directly solving the Pareto optimal solution of the dual-objective problem,and compare the solution results of the two methods.In this paper,the path optimization model of the muck truck will be solved in these two ways,and the solution results of the two ways will be compared.In terms of algorithm solution,the genetic algorithm and NSGA-II algorithm are used to solve the two multi-objective optimization problems respectively,and the genetic operators are improved accordingly according to the actual situation of the research problem in this paper.Through the optimization solution of the actual research area and transportation route,the Pareto optimal solution obtained by the multi-objective solution includes the unique optimal solution obtained by the singleobjective solution,and the transportation cost and transportation risk values of multiple optimal routes are obtained.Compared with the original transportation route,the transportation route is significantly lower,which confirms the rationality of the optimization model of the transportation route of the muck truck proposed in this paper and the effectiveness of the multi-objective solution method in the practical engineering application field.Provide a variety of different transportation route optimization schemes,which will help to further standardize the reasonable and standardized transportation of urban construction waste.