%0 Journal Article
	%A Hsin-Yi Huang and  Ming-Sheng Liu and  Jiun-Yan Shiau
	%D 2021
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 177, 2021
	%T Double Clustering as an Unsupervised Approach for Order Picking of Distributed Warehouses
	%U https://publications.waset.org/pdf/10012251
	%V 177
	%X Planning the order picking lists for warehouses to achieve some operational performances is a significant challenge when the costs associated with logistics are relatively high, and it is especially important in e-commerce era. Nowadays, many order planning techniques employ supervised machine learning algorithms. However, to define features for supervised machine learning algorithms is not a simple task. Against this background, we consider whether unsupervised algorithms can enhance the planning of order-picking lists. A double zone picking approach, which is based on using clustering algorithms twice, is developed. A simplified example is given to demonstrate the merit of our approach.
	%P 395 - 399