Research On Task Scheduling Of Multi-AGV System

Automated Guided Vehicle(AGV)is an automatic intelligent transportation equipment,which belongs to a type of mobile wheeled robot.AGV is one of the core components of modern logistics systems.It plays the role of porter in automated production lines or logistics systems.With the vigorous development of the e-commerce industry today,the warehousing and logistics system,which is one of its important components,also needs to be updated.Most warehouse logistics systems have the characteristics of short cycles,multiple batches,small single-time transportation,and complicated routes.In this context,traditional manual handling and forklift handling have gradually been replaced by AGV transportation systems.Therefore,it is of great practical significance to study a set of highly efficient task allocation schemes and AGV scheduling methods that can plan conflict-free shortest paths for multiple AGVs.In this paper,the task of multi-AGV task scheduling is studied in depth from the following three aspects:1.Establish a single-target task scheduling model with the minimum completion time as the optimization goal.By incorporating the improved genetic algorithm into the evolution system of the cultural algorithm group space,a hybrid cultural algorithm is proposed to solve and optimize the model,and pass The experimental comparison verifies the feasibility and superiority of the culture hybrid algorithm.2.On the basis of the single-objective model,a multi-objective task scheduling model with the task completion time,the number of AGVs,and the amount of task differences as optimization goals is established,and based on the cultural algorithm as the basic framework,an improved NSGA-III algorithm is proposed.Solve multi-objective problems.In the acceptance function,different targets are weighted to perform the same evaluation on different targets,and the mutation probability of the NSGA-III algorithm is dynamically adjusted through the influence function to prevent the algorithm from prematurely converging.The experimental comparison verifies that the improved algorithm has better optimization performance than the original algorithm.3.Combined with the previous research,by analyzing the floor plan of the example warehouse,a multi-objective model of multi-AGV task scheduling is established,and the model is solved and optimized using the improved NSGA-III algorithm,and finally a high-quality scheduling plan is obtained The algorithm in this paper can effectively solve the problem of multi-AGV task scheduling in complex environments.