Optimization Of Garbage Truck Collection And Transportation Path Based On Residents’ Satisfaction

With the development of economy and the abundance of materials,the production of domestic waste is increasing,and a large amount of garbage has put forward higher requirements for garbage collection and transportation.At the same time,residents have also put forward higher requirements for the service level of garbage collection and transportation.Complete garbage collection tasks quickly and efficiently,while trying to satisfy residents’ satisfaction.Therefore,scientifically and rationally arranging the collection and transportation path of garbage trucks can not only reduce the collection and transportation cost,complete the task efficiently,but also improve the satisfaction of residents.Based on the analysis of related research at home and abroad,this paper firstly introduces the relevant theories of the garbage collection and transportation system and vehicle routing.Taking the vehicle point routing problem of garbage collection and transportation as the research object,a suitable satisfaction model is selected,and the residents’ satisfaction A mathematical model is established with the goal of maximum and minimum transportation cost.Combined with the characteristics of the model,a non-dominated sorting genetic algorithm with an elite selection strategy is used to solve the problem.In order to make the algorithm more excellent,on the basis of the original NSGA-Ⅱ algorithm,the greedy idea is considered in the initial population stage to improve the local optimization ability,and at the same time,the local search algorithm is added to improve the quality of the solution.Then,using the spatial analysis function of the GIS software,the collection and transportation range and garbage collection points of a collection and transportation station in Lanzhou City are visualized.At the same time,according to the coordinates of each node,the OD distance matrix between any two points is obtained by using the GIS analysis tool..Finally,through the solution analysis of the specific example,the results before and after the optimization of the two algorithms are compared,and the results after the optimization of the algorithm are compared with the actual situation,and the following results are obtained:(1)It can be seen that the optimization result paths of the improved NSGA-Ⅱ algorithm are 6,the average full load rate is 90.6%,and the cost is 747.4 yuan;the optimization result paths of the NSGA-Ⅱ algorithm are 8,and the average full load rate is 65.6%.,the cost is 765 yuan.The improved algorithm saves 25% in the number of paths,the average full load rate is increased by 38.1%,and the cost is reduced by 2.3%.(2)Before optimization,the total collection cost of garbage trucks was 1100.23 yuan/day.After optimization using the NSGA-Ⅱ algorithm and the improved algorithm,the total collection cost was 765 yuan/day and 747.4 yuan/day.The total collection cost of garbage trucks was reduced respectively.335.23 yuan and 352.83 yuan,saving 30.5% and 32.1%respectively.(3)The transfer station originally used 3 to 4 compressed collection vehicles.A total of 9vehicles were dispatched every day.The average full load rate was 56.89%,and the full load rate of the vehicles was low.After the optimization of the NSGA-Ⅱ algorithm,the number of garbage collection points served by each vehicle has increased,and the average full load rate of the vehicle has reached 65.6% and 90.6%,respectively,which are 15.3% and 59.3% higher than before;The number of vehicles has been reduced from 3 to 2,and the number of vehicles has been reduced from 9 to 8 and 6,respectively.