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| Order Batch Optimization for “Part-to-Picker” Order Picking Systems |
| WANG Shanshan, ZHANG Jihui
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| a. Institute of Complexity Science; b. Shandong Key Laboratory of Industrial Control Technology, Qingdao University,Qingdao 266071,China |
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Abstract The frequency of bin entry and exit is one of the key factors affecting the efficiency of the “part-to-picker” picking system based on the shuttle storage system. In case of sufficient goods in the bin, the bins of a certain kind of goods required by the same batch of orders only need to be shipped out once. To allocate similar orders to one batch and to reduce the number of bins in and out of the warehouse can improve the picking efficiency of the system. Taking the minimum number of bins out of the warehouse as the objective function, an order batching optimization model is established. According to the characteristics of the model, an improved genetic algorithm is designed. A hybrid crossover strategy is proposed. On the basis of elite retention, partial search is performed on part of the elite chromosomes of each generation with a certain probability to improve the convergence speed and solution accuracy of genetic algorithm. The simulation results show that the total number of outgoing of bins is reduced after optimization, and the picking efficiency of the system is improved and the approach proposed is valid.
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Received: 01 February 2021
Published: 12 October 2022
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