Research And Implementation Of Optimized Scheduling For Automated Warehouses

Automated warehouse is the core component of contemporary logistics system.With the rapid development of economic globalization and e-commerce,the logistics industry is receiving more and more attention.In order to improve the efficiency of logistics and reduce the time cost of logistics,the research on the operational efficiency of automated warehouse has naturally become the top priority.The core means to improve the efficiency of automated warehouses is to optimize warehouse scheduling.Therefore,it is of great theoretical significance and engineering value to study the optimization scheduling problem of automated warehouse.Firstly,this thesis introduces the basic hardware model and software management system model of the automated warehouse studied in this thesis,and analyses the process of the warehouse entry and exit operation..At the same time,several common methods for modeling and simulation of discrete event dynamic systems are analyzed.The basic knowledge and advantages of the SimPy simulation library used in this thesis are introduced.SimPy simulation library is used to build an object-oriented simulation model for the automated warehouse studied in this thesis.While retaining the asynchronous and concurrent characteristics of the actual operation of the automated warehouse,the transfer of information flow is simplified.On this basis,the scheduling rules of automated warehouse are studied and put forward,including the allocation and scheduling rules of cargo location,RGV trolley scheduling rules,stacker delay rules and so on.An improved genetic algorithm is proposed to realize the optimal scheduling of automated warehouse by encoding the scheduling rules and finding the optimal solution.The GUI is encapsulated by the simulation model and the improved genetic algorithm of the automated warehouse.The GUI program after encapsulation is used to carry out the experiment.The experiment shows that the optimized scheduling rule set can significantly improve the operation efficiency of the automated warehouse.