An order picking optimization method based on hierarchical clustering
An optimization method and a hierarchical clustering technology, applied in the field of logistics management of goods in the warehouse, can solve the problems of low picking efficiency, repeated round-trips, waste of labor costs, etc., and achieve the effect of improving efficiency and reducing repeated round-trips
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[0023] like figure 1 As shown, the input order set X={x 1 ,x 2 ,...,x N}(each order x i It consists of a series of item numbers) represented by X, T, N in the figure, the minimum similarity within the group T (similar orders below this threshold will not be divided into the same group) and the maximum number of orders N (in practical application) depends on the maximum number of orders a cart can carry at one time);
[0024] (1) Assign a different group to each order, and demarcate a different group number;
[0025] (2) Jaccard distance is used to calculate the inter-group similarity of each two groups. If the combined intra-group similarity r1 of the two groups with the largest inter-group similarity is greater than or equal to T, then merge to generate a new group; loop the merger step;
[0026] Wherein, the similarity between two groups is determined by the average value of the order similarity between each order in one of the two groups and all orders in the other gr...
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