Research On Loading And Unloading Scheduling Algorithms Of Customized Furniture Automatic Sorting System

With the rapid development of economy and science and technology in China,people’s individualized demand is becoming more and more vigorous.Because the traditional largescale standardized furniture production mode can not meet the diversified needs of customers,it begins to change to multi-variety,small-batch and large-scale customized production mode.Compared with traditional furniture production methods,custom furniture has a variety of product types due to customer orders.In order to save the waste of raw material boards as much as possible,the boards of orders from multiple customers are integrated and cutted together.Although this production mode can effectively improve the utilization rate of raw material boards and save material costs,the boards of different customer orders will be piled up after processing,and the cost of subsequent sorting operations will increase.In this context,in order to improve sorting accuracy,improve sorting efficiency,reduce sorting time and labor cost,custom furniture manufacturers replace traditional inefficient manual sorting methods by introducing automatic sorting technology to realize the automatic sorting of boards.At present,most of the research on the scheduling strategy of the sorting system is focused on the manual order picking system and the automated storage and retrieval system.In a few studies on the strategy optimization method of automatic sorting system,it mainly focuses on item allocation,partition confluence and order sorting.Based on the urgent needs of the current custom furniture enterprises for the automatic sorting system’s loading and unloading scheduling control theory,the problem of the loading and unloading scheduling of the automatic sorting system under different scheduling situations is considered.The main research contents and results of this thesis are as follows:After assuming that all the boards of the order have been put into storage,the problem of unloading and packaging scheduling of the automatic sorting system in a deterministic environment is studied.Firstly,the problem of unloading and packing scheduling is abstracted into a three-stage flexible assembly flow shop scheduling problem with precedence constraints and machine constraints.Then,the weighted sum of the unloading makespan,the makespan in packing station,the total waiting time of board in packing station is minimized as the optimization goal,and the mathematical model of the problem is established.Based on the idea of solving multi-stage flexible flow shop scheduling problem,the multi-stage unloading and packing scheduling problem is decomposed in stages,and a heuristic algorithm H* is constructed to solve the problem.The simulation results show that compared with the combination.The simulation results show that compared with other heuristic algorithm,H* algorithm performs better.In order to improve the overall efficiency of the automatic sorting system,based on the problem of unloading and packing scheduling,considering the process of loading,this thesis studies the loading and unloading scheduling of the automatic sorting system in deterministic environment.Based on the mathematical model of the problem,a heuristic algorithm AH* is constructed.The core idea of the algorithm is to calculate the earliest and latest start loading time of each board according to the buffer capacity constraints.and in combination with the set buffer capacity constraint,and then arrange the start time of the inbound task based on the calculated inbound time interval.Then,based on the calculated loading time interval,the start time of the loading task is arranged.If the scheduled task conflicts with the unloading task,the affected operations rescheduling method is used to adjust the affected loading and unloading tasks.Simulation results demonstrate the effectiveness of the designed AH* algorithm for solving the problem.In order to be closer to the actual sorting operation environment,considering the uncertainty of the arrival time of the board in the sorting process,the loading and unloading scheduling problem of the automatic sorting system in the dynamic environment is studied.in order to cope with the disturbance of uncertain arrival time and respond to the buffer blocking exception,a rolling window rescheduling method based on variable period and event-driven is used to decompose the dynamic scheduling problem into several deterministic scheduling problems.After defining the rescheduling board task set of the problem,an loading and unloading rescheduling algorithm based on the warning line coefficient is proposed to solve the deterministic problem.The simulation results show that the algorithm with high warning line coefficient performs well in scheduling performance and scheduling stability.Based on the research results of the dynamic loading and unloading scheduling problem,considering the loading and unloading scheduling algorithm with the fixed warning line coefficient can not solve the scheduling problem under the changing state,and an adaptive scheduling problem is studied.Firstly,based on the research results of the current adaptive scheduling problem,an adaptive scheduling algorithm based on reinforcement learning is proposed.After defining the state space,reward function and action set of the Q learning algorithm corresponding to the problem,combined with the autonomy of Q learning.Based on the self-learning characteristics of Q learning,the self-adaptive scheduling algorithm can select the most appropriate warning line coefficients for different operation states of the sorting system.