Research On Optimization Strategy Of Automatic Storage And Retrieval System Based On Double Position Stacker

The rapid development of the logistics industry has led to a sharp increase in cargo volume and the complication of cargo management information in the 21 st century.The traditional simple and static warehouse management has been unable to meet the huge needs of the modern logistics industry,greatly affecting the efficiency of logistics and the company's economic benefits and market competitiveness.In recent years,the emergence of automated storage and retrieval system(AS/RS)has greatly reduced the inefficiencies,error-prone and unreasonable drawbacks of traditional warehouse manual management systems,improved the efficiency of warehouses.The most common form of warehouse in the warehousing industry is an AS/RS based on a single-station stacker.The tasks of this warehouse are completed by a single-station stacker fork.In one cycle of the compound operation using the single station fork,the operation of "storage" and "pick-up" can only be completed once,it is inefficient Then,the efficiency of goods retrieval and storage in logistics has been effectively improved due to rapid development of the AS/RS based on the double-station stacker,but there are still some problems such as unreasonable allocation of goods positions,unstable shelves,and low efficiency of storage and retrieval.Therefore,optimizing the position and path of the AS/RS based on the double-station stacker is conducive to improving the efficiency of goods storage and retrieval of the warehouse,as well as improve the operation quality and efficiency of the logistics industry.In this paper,the optimization of the AS/RS based on the double-station stacker is studied.The main research content includes two aspects: the optimization of the shelf and the optimization of the cargo access path.The experimental results show that the method studied in this paper can effectively improve the rationality of the cargo space allocation and the operating efficiency of the double-station stacker compound operation,which is of great significance to improve the efficiency of the cargo management of the AS/RS.The specific research contents of this paper are as follows:(1)In order to make the AS/RS location allocation model more accurate,the parameter of goods relevant is added to the model to optimize mathematical model of cargo location allocation based on the three parameters of the stability of shelves,the frequency of goods storage and retrieval,and the storage time of goods in the traditional model;Aiming at the shortcomings of "premature" and "local optimization" in the traditional genetic algorithm(GA)in the optimization of cargo location of AS/RS,this paper proposes an algorithm that uses RBF neural network to optimize the individual fitness function of genetic algorithm(RBF-GA algorithm),to realize the optimization of the cargo space of the AS/RS;(2)The strategy and model of variable-acceleration double-station stacker fork operation are proposed in this paper.The problems of starting,acceleration and braking are considered and the stability of the cargo on the double-station fork is studied.A more accurate mathematical model has been established to improve the automatic accuracy of the AS/RS;The initial population of GA is optimized by using ant colony algorithm(AC),and the selection operator,crossover operator and crossover strategy of traditional GA are improved to realize the optimization of the doublestation path compound operation.The simulation results show that,ant colony-improved genetic algorithm(AC-IGA)can faster and more accurately realize the optimization of the double-station composite operation path compared with the traditional GA.Compared with the path optimization before,the path time after optimization is significantly reduced.