Study On Job Scheduling Strategy Of Multi-AGV System In J Company

With the continuous improvement of the level of science and technology,the traditional high-volume production line production model has been unable to adapt to the uncertainty and variability of consumer terminals,and the requirements for flexible and intelligent production of enterprises are increasing.As an intelligent material handling vehicle,AGV shows high intelligence and automation in the workshop logistics,which greatly improves the flexibility of production in the manufacturing industry.However,due to the late start of AGV in domestic applications,there are still many problems in the using process.This paper takes J company's electronic control workshop multi-AGV system operation scheduling as the research object,and focuses on the problems of AGV in the path planning and task assignment in the material distribution process.This paper mainly studies the following aspects:(1)This paper investigates and studies job scheduling of multi-AGV system in electronic control workshop of J Company,collects research data,and finds out problems in path planning and task allocation in AGV distribution process through data analysis,and analyses the reasons for the problems.(2)In order to solve the problems in the process of AGV operation,this paper establishes a mathematical model aiming at the minimum AGV distribution distance in the system.In order to increases the scientific and practical nature of the mathematical model,this paper introduces the time window and the penalty function part according to the material consumption speed and the delivery time requirement in the production process of each production line.(3)In order to solve the mathematical model better,this paper analyses the commonly used algorithms and selects the particle swarm optimization algorithm to solve the model.Since the path improvement effect obtained by the particle swarm optimization algorithm is not obvious,the particle swarm-genetic hybrid algorithm is used to solve the problem,and the optimized path is obtained again.By analyzing and comparing the path before and after improvement,it is determined that the path obtained by solving the model by the particle swarm-genetic hybrid algorithm is the optimal path.(4)In order to prove the feasibility of the optimized path and visualize the improvement effect,Anylogic simulation software is used to simulate and compare the AGV distribution paths that before optimization and obtained by the particle swarm-genetic hybrid algorithm.By comparing the output data,it can be seen that the distribution path obtained by the particle swarm-genetic hybrid algorithm has a good effect,and the indicators are improved compared with before the optimization.This paper studies the operation scheduling of J company's multi-AGV system,re-planning the distribution path,making the AGV distribution path in the system more reasonable,improving the distribution efficiency and reducing the distribution cost.In this paper,there are 34 figures,28 tables,83 references.