Research On Optimization Method For Storage Position Of Cantilever Shelf Stereoscopic Warehouse

As a special kind of automated warehouse,cantilever rack stereoscopic warehouses are widely used in the building-materials industry and manufacturing industry.For instances,the production of plate-type custom furniture includes an process of ordering and sorting the packages after the sheet is processed;However,the manual ordering and sorting way suffers from a large cache area,high labor intensity,low efficiency,and high costs.As an important sorting tool,the cantilever rack stereoscopic warehouse serves the functions of caching and sorting.Since the cargo space size can be dynamically adjusted and allocated,it is of great significance for saving the production cost and meticulous production to improve the utilization rate of the cantilever rack stereoscopic warehouse and the storage operation efficiency.The key to improve the performance of cantilever rack stereoscopic warehouse lies in the optimization of storage space.For the space optimization of cantilever rack stereoscopic warehouse,this paper identifies its two sub-problems,namely,the static storage space allocation of cantilever rack stereoscopic warehouse and the dynamic location optimization of sorting operations in industrial production.These two independent and complementary processes constitute a complete space allocation solution for production of plate-type cantilever rack stereoscopic warehouse.The specific study is detailed as follows:With respect to the problem of static storage space allocation for cantilever rack stereoscopic warehouse,this paper proposes a space allocation strategy that aims to improve the efficiency,stability,and security of the three-dimensional warehouse,and establishes a corresponding objective function model of total amount of shelves and the overall center of gravity of the shelves.Then,a multi-group genetic algorithm is proposed to optimize the model to effectively improve the utilization and stability of cantilever rack stereoscopic warehouse.In detail,to solve the problems such as premature convergence and slow convergence in the solution of cantilever shelf three-dimensional warehouse storage space allocation in typical multi-group genetic algorithm,a hybrid strategy of fitness function scaling and control parameter adaptation is proposed.The results of comparison show that the multi-group genetic algorithm is superior to the simple genetic algorithm in terms of global searching ability and convergence speed for the problem of static storage space allocation in cantilever shelf stereo warehouses.With respect to the processing order intensive-constrained real-time dynamic location allocation problem of cantilever rack stereoscopic warehouse,a mathematical model of sorting operation is established with the aim of a shortest overall storage time and a highest sorting operation efficiency of the stereoscopic warehouse stacker.Three sorting operations(including cargo position strategy,nearest neighbor strategy,and classification strategy)are applied to optimize the real-time position of cargo to support rapid sorting.Simulations of system logistics are used to perform the real-time position optimization strategies for the three sorting operations.Experimental analysis shows that the nearest cargo location strategy has a significant impact on the efficiency of sorting operations under the intensive constraints of processing sequences.Considering the problems such as ignoring some unknown factors in simplification of the model in the simulation testing technology,a system logistics simulation scheme that combining a physical logistics simulation model with a physical control system is proposed.Taking the sorting operation of a panel-type customized furniture production as a case,the physical communication network is presented to connect the 1:1 three-dimensional logistics simulation model with the physical control system,which greatly improves the authenticity and reliability of the simulation results.