Abstract
At Kunming International Flower Auction Market (KIFA), about 2.5 million cut flowers traded in 10,000 transactions need to be distributed daily to buyers in its distribution area. Small lots and many buyers per trolley are two distinctive features at KIFA and the identities of the buyers and their demands are not known in advance. The growing transaction volume has recently increased the distribution workforce and the buyers’ waiting time. In this paper, we introduce a modified class-based location policy using KIFA’s historical data to improve its current put system performance. We use the closest-open location method in each class area, which improves the put system performance at KIFA. We examine the effects of the distribution area shape and the number of blocks in each class area on performance measures, and find that KIFA’s put system performance can be further improved.
Acknowledgements
This work was partially supported by the National Natural Science Foundation of China (NSFC) [grant number 71001073, 71062006, 71162019, 71390335, 71471118], by the Humanities and Social Sciences Foundation of Ministry of Education of China [grant number 14YJC630096], by the Distinguished University Young Scholar Program of Guangdong Province [grant number Yq2013140]. We also thank the anonymous reviewers and the editor for their helpful comments, which improve the exposition of this paper.