Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Research of Order Batching Variable Neighborhood Search Algorithm based on Saving Mileage

Authors
Zeping Pei, Zhuan Wang, Yiwen Yang
Corresponding Author
Zeping Pei
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.34How to use a DOI?
Keywords
order batching; mileage saving; routing optimization; variable neighborhood search algorithm.
Abstract
Basing on a picker-to-parts batch picking system of full container load, an order batching model takes picking equipment and commodity packaging volume into consideration is constructed, the objective of the model is to maximize the saving mileage. To solve the model, an order batching variable neighborhood search algorithm is proposed. With the data from a specific logistic center, a simulation experiment has been carried out. The results show that, the performance of VNS-Deco is superior to FCFS, SBBM and S&U-Deco under 4 different order pool situations, the total picking mileage optimized by VNS-Deco is reduced by 13.2%, 3.3% and 1.6% compared with FCFS, SBBM and S&U-Deco.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.34How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zeping Pei
AU  - Zhuan Wang
AU  - Yiwen Yang
PY  - 2019/04
DA  - 2019/04
TI  - Research of Order Batching Variable Neighborhood Search Algorithm based on Saving Mileage
BT  - 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 196
EP  - 203
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.34
DO  - https://doi.org/10.2991/icmeit-19.2019.34
ID  - Pei2019/04
ER  -