Research on Order Batch Optimization Based on Comprehensive Lane Similarity

DOI

10.2991/978-94-6463-308-5_34How to use a DOI?

Keywords

order similarity; seed algorithm; order batching; e-commerce warehouse

Abstract

Reasonable order batching methods can improve the efficiency of picking operations in warehouses, and order batching through aisle similarity is one of the ways. However, in the existing research on dual-zone e-commerce warehouses, the order batching optimization based on aisle similarity does not consider regional information, which increases the number of aisles passed during picking, longer walking paths for pickers, and an increase in picking operation time. In this paper, we propose a comprehensive lane similarity measure for the AB zone considering regional information and design an order-batching heuristic seed algorithm for solving the problem. The experimental results show that the model and method can significantly shorten the order picking operation time and improve the picking efficiency.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Chenxia Jin
AU  - Xi Wei
AU  - Baozhen Guo
PY  - 2023
DA  - 2023/12/11
TI  - Research on Order Batch Optimization Based on Comprehensive Lane Similarity
BT  - Proceedings of the 2023 8th International Conference on Engineering Management (ICEM 2023)
PB  - Atlantis Press
SP  - 317
EP  - 325
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-308-5_34
DO  - 10.2991/978-94-6463-308-5_34
ID  - Jin2023
ER  -