Abstract: The “part-to-picker” picking system always adopts the picking mode described as “Out Stock-Picking-In Stock”, the key factor to restraint the picking efficiency is the frequency of “In-Out Stock”. The order sequence optimization model is proposed to decrease the frequency of “In-Out Stock” and improve the picking efficiency of the system. The order coupled factor is defined to represent the number of common SKU asked by two orders and can be placed in the temporary storage location. The model is built for order sequence optimization problem with the order coupled factor. In this model, the optimization object is transferred from improving picking efficiency to decreasing the frequency of “In-Out Stock”. The order sequence optimization problem in each picking station can be classified to the travelling salesman problem(TSP). An improved K-Means clustering algorithm is designed to solve the model. First, the coupled factor is calculated and sorted; then the orders is assigned to each picking station and sequenced to minimized the summation of the coupled factor of all orders. It is shown by the simulation that the picking efficiency can be improved by 15.9%.

Key words: clustering, coupled, order sequence, part-to-picker, picking