Analysis of Computational Efficiency in Iterative Order Batching Optimization

Johan Oxenstierna, Johan Oxenstierna, Jacek Malec, Volker Krueger

2022

Abstract

Order Picking in warehouses is often optimized through a method known as Order Batching, wherein several orders can be assigned to be picked by the same vehicle. Although there exists a rich body of research on Order Batching optimization, one area which demands more attention is that of computational efficiency, especially for warehouses with unconventional layouts and vehicle capacity configurations. Due to the NP-hard nature of Order Batching, computational cost for optimally solving large instances is often prohibitive. In this paper we focus on approximate optimization and study the rate of improvement over a baseline solution until a timeout, using the Single Batch Iterated (SBI) algorithm. Modifications to the algorithm, trading computational efficiency against increased memory usage, are tested and discussed. Existing and newly generated benchmark datasets are used to evaluate the algorithm on various scenarios. On smaller instances we corroborate previous findings that results within a few percentage points of optimality are obtainable at minimal CPU-time. For larger instances we find that solution improvement continues throughout the allotted time but at a rate which is difficult to justify in many operational scenarios. The relevance of the results within Industry 4.0 era warehouse operations is discussed.

Paper Citation

in Harvard Style

Oxenstierna J., Malec J. and Krueger V. (2022). Analysis of Computational Efficiency in Iterative Order Batching Optimization. In Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-548-7, pages 345-353. DOI: 10.5220/0010837700003117

in Bibtex Style

@conference{icores22,
author={Johan Oxenstierna and Jacek Malec and Volker Krueger},
title={Analysis of Computational Efficiency in Iterative Order Batching Optimization},
booktitle={Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2022},
pages={345-353},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010837700003117},
isbn={978-989-758-548-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Analysis of Computational Efficiency in Iterative Order Batching Optimization
SN - 978-989-758-548-7
AU - Oxenstierna J.
AU - Malec J.
AU - Krueger V.
PY - 2022
SP - 345
EP - 353
DO - 10.5220/0010837700003117