Research On Integrated Optimization For Job-shop Scheduling Of Automated Guided Vehicles Path Planning

AGV is an intelligent logistics equipment which could satisfy the needs of automation high-flexible high-efficiency high reliability and concurrent job.However,the research of flexible job shop mainly focuses on production scheduling,while ignoring the impact of AGV logistics transfer: Only focuses on production scheduling may cause the AGV path to not be optimal;Only focuses on the AGV path may cause impractical scheduling optimization results and make an impact on the processing process of the flexible workshop.Therefore,It is necessary to research on path planning optimization,scheduling model optimization,etc.Integrating the AGV path planning and the production scheduling optimization to improve the production efficiency of the enterprise.this paper that based on the AGV path planning algorithm and scheduling algorithm of Petri net model has carried out the following research work:(1)Aiming at AGV path planning algorithm problem that have impractical mathematical model and inefficiency solving the large-scale problem.Combining AGV path planning problem feature with mathematical model that consider vehicle capacity and time window.Meanwhile,proposing two improved genetic algorithms for vehicle routing problems in the algorithm design process.Solving the problem that genetic algorithm is prone to produce infeasible solutions and the efficiency of solving large-scale models is inefficiency,and the test case is compared with the existing algorithm to verify the feasibility and effectiveness.(2)Aiming at the Petri net model of flexible job shop,a two-stage hybrid search algorithm is proposed.It combined by A* and beam search,is proposed to overcome the limitations of common method of Petri net search.In the first-stage,the search space is pruned by using beam search algorithms.In the second-stage,a feasible suboptimal path is selected by depth-first search algorithm.Two benchmarks instances from literature,which were used to two instance to test the performances of the proposed algorithm.The comparative tests show the algorithm can get better quality schedules with lower memory requirements and computing times,by compared with other algorithms.(3)Based on dynamic scheduling strategy,production scheduling and AGV integration problem optimized to dynamic scheduling strategy.Regarding job-shop orders intermittent arrival and uncertainty events occurrence,this paper put forward the dynamic scheduling strategy of event-driven and cyclical-driven rolling window techniques.With the dynamic algorithm that convert dynamic scheduling problems,to solve static scheduling problems.Experimental results show that the dynamic scheduling method could effort to the scheduling problem of machine failures and new order.