The problem of batching orders and routing orders in picker-to-parts warehouses is intensively studied in the research literature, but the impact of individual differences among pickers or forklift operators and their skills are rarely taken into consideration. Therefore, we propose a model that simultaneously does order batching and routing while taking advantage of the skills of each worker. This approach optimizes the total batch execution time, and reduces the physical and mental effort of workers, since they are likely to perform easy tasks according to their capabilities. Based on empirical data on workers' skills and tasks characteristics, we present an integer linear programming model based on the classic joint order batching and picker routing problem, with the novelty that individual workers' skills are taken into account while assigning tasks to workers. Using real-world instances, the computational experiments show that it is possible to solve instances with up to 20 orders to proven optimality within a time limit of 1 hour, without considerably increasing the total distance traveled compared to the classic approach which only focuses on minimizing this criterion.

Jamal, J., Loske, D., Klumpp, M., Chou, X., Di Florio Di Renzo, A., Dell'Amico, M., et al. (2022). Skill-Based Joint Order Batching and Picker Routing Problem. In ACM International Conference Proceeding Series (pp.64-69). Association for Computing Machinery [10.1145/3523132.3523143].

Skill-Based Joint Order Batching and Picker Routing Problem

Chou, X;
2022

Abstract

The problem of batching orders and routing orders in picker-to-parts warehouses is intensively studied in the research literature, but the impact of individual differences among pickers or forklift operators and their skills are rarely taken into consideration. Therefore, we propose a model that simultaneously does order batching and routing while taking advantage of the skills of each worker. This approach optimizes the total batch execution time, and reduces the physical and mental effort of workers, since they are likely to perform easy tasks according to their capabilities. Based on empirical data on workers' skills and tasks characteristics, we present an integer linear programming model based on the classic joint order batching and picker routing problem, with the novelty that individual workers' skills are taken into account while assigning tasks to workers. Using real-world instances, the computational experiments show that it is possible to solve instances with up to 20 orders to proven optimality within a time limit of 1 hour, without considerably increasing the total distance traveled compared to the classic approach which only focuses on minimizing this criterion.
paper
logistics; order batching; order picking; routing;
English
9th International Conference on Industrial Engineering and Applications, ICIEA 2022-Europe - 12 January 2022 through 14 January 2022
2022
ACM International Conference Proceeding Series
9781450396059
2022
64
69
none
Jamal, J., Loske, D., Klumpp, M., Chou, X., Di Florio Di Renzo, A., Dell'Amico, M., et al. (2022). Skill-Based Joint Order Batching and Picker Routing Problem. In ACM International Conference Proceeding Series (pp.64-69). Association for Computing Machinery [10.1145/3523132.3523143].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/467049
Citazioni
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
Social impact