Research Of Strategy On Automated Guided Vehicle System Task Scheduling

With the rise of e-commerce and other emerging formats, the uncertainty of consumer demand gradually increased. In order to improve market responsiveness and profitability, the production of manufacturing enterprises change from mass and batch production to cell production,customization and flexible production. Flexible manufacturing will be more dependent on flexible logistics system, AGV as a logistics and transport equipment integrating characters of automation, informatization and intelligence, it will assume an important role in the current and future manufacturing fields, and services of AGV can extends to every corner of the enterprise logistics. Task Scheduling of AGV system will become the primary problem.Based on the study of domestic and foreign scholars, this paper, task scheduling problem of multi-AGV system is studied. The goal is Task balancing (workload balancing) and conflict-free path planning, in the framework of particle swarm algorithm, and then build the mathematical model. Steps of scheduling algorithm also be proposed, and finally verified by simulation analysis.This paper analyzes the operating environment of AGV system, select the most representative and then established a model of the environment, based which to established the task allocation strategy and path optimization strategies.Task allocation principle is "FIFO". In ensuring the efficiency of the premise, this paper introduces the task priority of the task sequence to sort and assign it to a AGV has normal state (no fault, no power shortage); In addition, evaluate the status of tasks implementation can further optimization strategies tasking. This avoids backlog AGV task which led to delays in the overall efficiency of the system. Also, it could then judge whether you need to increase the number of AGV in the system to ease the backlog of tasks. Principle of path planning is conflict-free, the goal is the shortest. This paper summarizes the AGV conflicts that may arise during the operation, and then adjust based on the geometric path and speed adjustment to achieve conflict avoidance; By detecting the AGV operating conditions, and then combined with the priority tasks,we can fine-tune the AGV dynamic path. It can enforcement AGV system to deal with the conflict of path by pre-planning and on-line adjustment of policy. Finally, the objective function is the shortest time to complete the task of the entire batch, then build AGV System Operation mathematical model by adding constraints to ensure a balanced distribution of tasks and task prioritization.Since particle swarm algorithm can be programmed to achieve easily, and it has fast convergence and high precision, this paper finally selected PSO as framework after careful comparison. By correcting operator, given the scheduling algorithm steps, and finally verified by simulation analysis. Simulation results show that, in meet the premise of conflict-free pathing, AGV system can be realized in the shortest time to complete all the tasks, and achieve a more balanced distribution of tasks AGV system, proved the effectiveness of ideas.