关键词: 智能仓库, AGV, 订单分批, 整数规划模型, 加权相似度, 贪婪算法

Abstract: The problem of order batching in parts-to-picker intelligent warehouse based on automatic guided vehicle(AGV)is studied. The costs of workers picking items from shelves and the costs of AGV transporting shelves are considered simultaneously. An integer programming model of order batching problem is established to minimize the total costs. Based on the items contained in each order and the shelves where the items of an order are stored, the weighted similarity is formulated to describe the relationship between orders. The positive correlation between weighted similarity and total picking cost is analyzed. Based on the weighted similarity between orders, a greedy algorithm for solving the model is designed. The simulation is done on a specific example. The sensitivity analysis of weighted coefficient is done. The influence of weighting coefficient change on batching results, and the relationship among the value of and the cost of λ worker picking one item c₁ and the cost of AGV moving one shelf c₂ are analyzed. The results show that the approximate optimal solution of the order batching problem can be obtained in a short time by using the greedy algorithm with appropriate weighting coefficient. For small scale examples, the approximate ratio is less than 1.35 in the worst case. Using the model and algorithm in this paper for order batching, two types of costs are considered at the same time, which can effectively improve the efficiency and reduce the total costs of order picking.

Key words: intelligent warehouse, AGV, order batching, integer programming model, weighted similarity, greedy algorithm