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A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse. (English) Zbl 1304.90040
Summary: Batching customer orders in a warehouse can result in considerable savings in order pickers’ travel distances. Many picker-to-parts warehouses have precedence constraints in picking a customer order. In this paper a joint order-batching and picker routing method is introduced to solve this combined precedence-constrained routing and order-batching problem. It consists of two sub-algorithms: an optimal \(A^\ast\)-algorithm for the routing; and a simulated annealing algorithm for the batching which estimates the savings gained from batching more than two customer orders to avoid unnecessary routing. For batches of three customer orders, the introduced algorithm produces results with an error of less than 1.2% compared to the optimal solution. It also compares well to other heuristics from literature. A data set from a large Finnish order picking warehouse is rerouted and rebatched resulting in savings of over 5000kilometres or 16% in travel distance in 3months compared to the current method.

90B06 Transportation, logistics and supply chain management
90C59 Approximation methods and heuristics in mathematical programming
90B90 Case-oriented studies in operations research
Full Text: DOI
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