Research On Job Shop Scheduling Problem Under AGV Constraints

The study of job shop scheduling has been the key research object in modern manufacturing industry.The main purpose of workshop scheduling is to optimize the production time or cost of products under various constraints.Some scholars put forward the flexible job shop scheduling problem,that is,flexible job workshop scheduling.The flexibility of the machine means that the machine can realize a variety of operations,that is,each operation has several multiple processing machines to choose.Each operation can be handled on one of the machines.With the increase in labor costs in China,many factories are more and more inclined to use AGV for material handling in workshops.AGV handling is becoming the mainstream of material handling in modern manufacturing workshops.AGV and machine integration scheduling problem is gradually becoming an important research problem in job shop scheduling.(1)The workshop scheduling problem without AGV constraints is modeled.The population initialization,adaptive variation and excellent individual neighborhood search are increased in the traditional genetic algorithm,which improve the efficiency and search ability of the algorithm.Finally,the cases which belong to the job shop scheduling standard case base are solved.The improved genetic algorithm is used to solve the case problem in the standard case base of job shop scheduling.The experimental results show that the improved algorithm can complete the task well.(2)A FJSP model considering AGV handling independent of process is established.An improved multi-population genetic algorithm is designed to solve the problem by using migration operator to coordinate various groups to advance and setting up an essence population to preserve the best individuals in all populations.By comparing the cases of known literature,the comparison chart of changes in the results of the solution and optimized scheduling scheme and are obtained.The results show that the algorithm can get the optimal solution faster and better than the traditional genetic algorithm,and it is also superior to the test results in the known literature.(3)The mathematical model of job shop scheduling under multiple AG Vs constraints is established to solve the FJSP under multiple AGVs constraints.The heuristic scheduling method is used to allocate the required AGV before processing,and the optimal allocation strategy is used to select the AGV handling workpiece.The variation and cross operation in differential evolution algorithm are improved so that the improved algorithm can be searched directly in the global range of discretization.The variable neighborhood search algorithm is embedded in the improved differential evolution algorithm,so that the better quality solution can be obtained in the neighborhood range.Experimental results prove the effectiveness,stability and superiority of the improved differential evolution algorithm for solving FJSP under multiple AGVs constraints.(4)This paper studies the job shop scheduling problem under multiple AGVs constraints,which consider the production situation of glass thinning workshop in P company.This paper analyzes the layout of glass thinning workshop in P company,plans the AGV scheduling road map in the workshop,and designs a multiple AGVs constrained workshop management system based on the MATLAB software.