Optimizing the logistic order-picking process in the distribution center depends on two closely related decisions: how to schedule the processing of orders by a limited number of employees and how to sequence the containers on the conveyor to be transported to the buffers where they can be serviced. The main aim of this research is to develop a heuristic solution approach for the logistic order-picking problem with sequence-dependent constraints and a one-directional conveyor. The developed heuristics allow for minimizing the total time needed to process all orders. Central to this approach is decomposing the order-picking problem and finding the product quantity using mathematical programming. Next, using product quantity as an input value, find the container start time implementing heuristics. The performance criterion is time; thus, in the developed Pickers and Buffers heuristics, the execution time of each one is less than a second. A comprehensive computational study demonstrates the numerical advantage of the proposed heuristic approach in most instances compared to the solution of the initial and reduced models obtained with the commercial solver. On the one hand, for small instances, Pickers heuristics were better on average 50.17%, Buffers heuristics were better on average 50.87% compared to the initial model for different layouts. For large instances, both heuristics showed 100%. On the other hand, compared to the reduced model, Pickers heuristics were better on average 35.91%, Buffers heuristics were better on average 36.16% for different layouts for different instances.
Heuristics for the Order-Picking Problem With Sequence-Dependent Constraints and a One-Directional Conveyor
Kateryna Czerniachowska,Marcin Hernes
Published 2025 in IEEE Access
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2025
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IEEE Access
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Business, Engineering, Computer Science
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