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

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.