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This article aimed to study the real-world order-picking problem in a warehouse at a shoe manufacturing company. We observed essential characteristics of the environment, such as random storage locations for the same SKU and aisle-constrained travel distances, as variants of the problem under study. The objective was to minimize the total wave-picking distance. We defined the problem statement and proposed some methods for modeling and solving it, including constructive techniques, mathematical programming approaches such as mixed-integer linear programming, and two new constraint programming models. For the computational tests, we ran the methods on robust data from real-world instances given by the company's warehouse system and compared them with the company's actual approach. The results showed that the proposed constraint programming method with interval variables provided high-quality solutions with computational efficiency and was competitive with methods in the literature.
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