Ant Colony Optimization for Storage Recombination Problem

In a company, warehousing accounts for 20% of the operating costs and picking operations account for 50% of storage costs. Therefore, storage through the reorganization can be effectively reused these spaces, thereby affecting the follow-up operation of the warehouse staff picking operation time. In this study, after the rearrangement of storage spaces, the optimal spatial applications are sorted out. By constructing the mathematical programming model of problems and using the ant algorithm to solve the storage and the reconstruction path problem. Within a reasonable range of costs, a systematic solution method is developed to solve the "minimizing the moving distance" and find the optimal path by applying the mathematical model of the distance of storage and reorganization moving. There are two stages in this study, the first phase is based on the existing data, to calculate the ratio and the distance of the storage space, according to the calculation and reconstruction of storage after the reorganization of data to make an adjustment of the storage area of ​​all storage status of the empty state of storage increased in the second stage, the storage location that needs to be stored and rebuilt is solved by the ant algorithm to find the shortest path. The simulation results suggest that this method is compared with the existing storage location reorganization mode. After the algorithm is actuated to (1) The method can increase the number of storage spaces and (2) the storage and reconstruction of the shorter moving distance and the results of this study can provide some reference for the warehouse staff.