4.5 Article

The study of joint order batching and picker routing problem with food and nonfood category constraint in online-to-offline grocery store

Journal

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
Volume 28, Issue 5, Pages 2440-2463

Publisher

WILEY
DOI: 10.1111/itor.12926

Keywords

warehouse management; order picking; batch‐ routing problem; category constraint; seed algorithms

Funding

  1. National Natural Science Foundation of China [71801105]
  2. China Ministry of Education Social Sciences and Humanities Research Youth Fund Project [18YJC630242]
  3. China Postdoctoral Science Foundation [2017M622488]

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Order picking process accounts for more than 55% of total warehouse cost, with the JOBPRP being an effective way to improve efficiency. This study focuses on JOBPRP with category constraint to minimize processing time, utilizing modified seed algorithms and routing methods for better performance. Recommended storage assignment strategies involve separating nonfood and food products into fewer zones for optimal results.
Order picking is the process of retrieving products from the storage locations to meet customer orders, which accounts for more than 55% of the total warehouse cost. The joint order batching and picker routing problem (JOBPRP) is an effective way to improve picking efficiency. Although many warehouses face the physical constraints of products that have impact on the picking sequence, such as weight, size, shape, and fragility, JOBPRP with such physical constraints has not been widely studied in the literature. This paper is inspired by a practical case observed in an online-to-offline grocery store in China, where food products should not be carried under nonfood products in the picking container to maintain food safety, called category constraint. Therefore, JOBPRP with category constraint is studied. The JOBPRP optimization models with and without category constraint are formulated to minimize the total processing time, and the modified seed algorithms, with new seed addition rules and modified near-optimal routing methods are proposed to solve the models. The performance of the proposed algorithms is evaluated in different seed addition rules, routing methods, sort time scenarios, and storage assignment strategies (SASs) in a case study. We found that considering category constraint in JOBPRP can reduce the total processing time, and the modified seed algorithms perform better than the traditional first-come-first-serve benchmark algorithms and the seed algorithms with traditional seed addition rules and S-shape routing method. The SASs where nonfood and food products are separately in fewer number of zones are recommended.

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