Research On Location Selection Of Waste Collection-route Problem

The sorting and disposal of garbage is of great significance to our lives,and it can help us save resources and reduce environmental pollution.The current research on waste removal and transportation still focuses on the problem of location selection and path planning under a fixed amount of waste generation,and the uncertainty of the problem is not considered in the model design.In real life,the amount of garbage generated in each residential area is not a fixed value,and the randomness of the amount of garbage often leads to changes in the removal plan.To reduce the overall cleaning and transportation costs,the cleaning and transportation routes cannot be too long,which requires the construction of garbage treatment facilities not to be too far away;and if the treatment facilities are too close to the residential area,it will arouse the resentment of residents.These two economic goals and Social goals are in conflict with each other and need to be handled as a multi-objective optimization problem.At the same time,most of the current researches generally do not pay much attention to the effectiveness of the algorithm in the later iterations and the diversity of the population when using various evolutionary algorithms to solve related problems,which leads to inefficient algorithm iterations and easy loss of better feasible solutions.This paper considers the actual garbage collection problem in real life,improves the model design,and establishes a mathematical model of the garbage removal site selection-path planning problem under the non-deterministic demand.In the model,the amount of garbage generated by the customer site is of various types and is randomly generated according to a normal distribution.The garbage truck starts from the parking lot and arrives at the customer site before knowing the specific amount of garbage that needs to be removed.Garbage is transported to different garbage treatment facilities for processing.The mathematical model proposed includes two objective functions.One is the economic objective function: to minimize the economic cost(including the cost of transporting trucks,the construction cost of garbage dumps,and the construction cost of garbage treatment facilities);the other is the social objective function(garbage treatment facilities).The distance to the customer point should be as far as possible.After comprehensively considering the actual problems of garbage removal and transportation and modeling,this paper proposes an improved non-dominated sorting genetic algorithm(IMNSGA-Ⅱ)to locate the location of garbage truck yards and garbage treatment facilities,and design complete vehicle driving routes.The structure of the traditional initial solution is changed,and the clustering method is used to generate a good initial solution;an adaptive strategy is constructed to dynamically control the value of the crossover probability and the mutation probability,so as to avoid the algorithm from falling into the local optimum in the later iteration.The global search capability of the algorithm is enhanced.In addition,three multi-objective decomposition methods are used: Weighted sum algorithm(WS),Goal programming method(GP)and Goal attainment method(GA)to verify the performance of the algorithm,and use 4 Two evaluation indicators compare the results obtained by the algorithm.Through experiments on 120 test data sets with real geographical locations in Beijing,the effectiveness of the proposed improved NSGA-Ⅱ algorithm(IMNSGA-Ⅱ)in solving practical problems is verified.