@inproceedings{bbb2cb6abdee4b3384af5d2c8fde875d,
title = "A data mining technique to grouping customer orders in warehouse management system",
abstract = "Warehouse management system (WMS) today is viewed as a basis to reinforcing company logistics. Order picking is one of the routine operations in warehouses. Before picking a large amount of orders, effectively grouping orders into batches can speed up product movement within the warehouse. Several batching heuristics have been proposed in the literature for minimizing travel distance or travel time. This paper presents an order batching approach in a distribution center with a parallel-aisle layout. A heuristic order batching approach based on data mining is developed in this paper.",
author = "Mu-Chen Chen and Huang, {Cheng Lung} and Wu, {Hsiao Pin} and Hsu, {Ming Fu} and Hsu, {Fei Hou}",
year = "2005",
month = dec,
day = "1",
doi = "10.1007/3-540-32391-0_109",
language = "English",
isbn = "3540250557",
series = "Advances in Soft Computing",
number = "AISC",
pages = "1063--1070",
booktitle = "Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005",
edition = "AISC",
note = "4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005 ; Conference date: 25-05-2005 Through 27-05-2005",
}