Order batching using an approximation for the distance travelled by pickers

Authors: Cristiano Arbex Valle, John E Beasley

Results of the summarizing process for the arXiv paper: 1808.00499v4

  • Comprehensive Summary
  • Key points
  • Layman's Summary
  • Blog article
The summary is not ready yet

Abstract: In this paper we investigate the problem of order batching for picker routing. Our approach is applicable to warehouses (storage areas) arranged in the standard rectangular grid layout, so with parallel aisles and two or more cross-aisles. The motivation underlying our work is online grocery shopping in which orders may be composed of dozens of items. The approach presented directly addresses order batching, but uses a distance approximation to influence the batching of orders without directly addressing the routing problem. We present a basic formulation based on deciding the orders to be batched together so as to optimise an objective that approximates the picker routing distance travelled. We extend our formulation by improving the approximation for cases where we have more than one block in the warehouse. We present constraints to remove symmetry in order to lessen the computational effort required, as well as constraints that significantly improve the value of the linear programming relaxation of our formulation. A heuristic algorithm based on partial integer optimisation of our mathematical formulation is also presented. Once order batching has been decided we optimally route each individual picker using a previous approach presented in the literature. Extensive computational results for publicly available test problems involving up to 75 orders are given for both single and multiple block warehouse configurations.

Submitted to arXiv on 01 Aug. 2018

Tools for this paper

Explain it differently 3 free rewrites left today
Export BibTeX · RIS (Zotero, Mendeley, EndNote) · Markdown (Notion, Obsidian) · Premium
Citation alerts Premium
Journal club Slides to present it Premium
For journalists Press kit and hype check Premium

Ask questions about this paper to our AI assistant

You can also chat with multiple papers at once here.

⚠The license of the paper does not allow us to build upon its content and the AI assistant only knows about the paper metadata rather than the full article.

Figures and plots

Ask about a figure by number or use its question button to request visual analysis. Up to two figures and four image panels per question. Values read from plots are approximate; check the original data.

AI assistant instructions?

Assess the quality of the AI-generated content by voting

Score: 0

Why do we need votes?

Votes are used to determine whether we need to re-run our summarizing tools. If the count reaches -10, our tools can be restarted.

The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.

⚠The license of this specific paper does not allow us to build upon its content and the summarizing tools will be run using the paper metadata rather than the full article. However, it still does a good job, and you can also try our tools on papers with more open licenses.

Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.