The Effect of Order Batching on a Cyclical Order Picking System

Hofmann, Flora; Visagie, Stephan E.

doi:10.1007/978-3-030-87672-2_17

Cited by 1 publication

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Constraints (7) mean that the requests of article p must be satisfied, while Constraints (8) indicate that all the demands of customer i must be satisfied. Constraints (9) guarantee that the picking process of batch b ends at the sum of its starting time and the total time devoted to the task. Constraints (10) say that the finishing time of an order i is the longest completion time of the batches for this order.…”

Section: Bi-objective Obp-opp Modelmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System

Miguel,

Frutos,

Méndez

et al. 2024

Mathematics

View full text Add to dashboard Cite

This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.

show abstract

Section: Bi-objective Obp-opp Modelmentioning

confidence: 99%

“…The preparation of orders requires picking up goods from certain storage areas in response to specific requests made by customers [6][7][8][9][10]. These processes cover the most expensive tasks in most warehouses, namely picking-up the requests from their sites of storage and conveying them to the preparation/dispatch area [11][12][13].…”

Section: Introductionmentioning

confidence: 99%