Metaheuristics for the Order Batching Problem in Manual Order Picking Systems
AbstractIn manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations effciently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem; the rst one is based on Iterated Local Search, the second one on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods, but provide solutions which may allow for operating distribution warehouses signi cantly more effcient.
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Bibliographic InfoPaper provided by Otto-von-Guericke University Magdeburg, Faculty of Economics and Management in its series FEMM Working Papers with number 09020.
Length: 28 pages
Date of creation: Jun 2009
Date of revision:
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Warehouse Management; Order Picking; Order Batching; Iterated Local Search; Ant Colony Optimization;
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- Stutzle, Thomas, 2006. "Iterated local search for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1519-1539, November.
- Gibson, David R. & Sharp, Gunter P., 1992. "Order batching procedures," European Journal of Operational Research, Elsevier, vol. 58(1), pages 57-67, April.
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