Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103688
Authors: 
Henn, Sebastian
Koch, Sören
Doerner, Karl F.
Strauss, Christine
Wäscher, Gerhard
Year of Publication: 
2010
Citation: 
[Journal:] BuR - Business Research [ISSN:] 1866-8658 [Volume:] 3 [Year:] 2010 [Issue:] 1 [Pages:] 82-105
Abstract: 
In 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 efficiently, 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 first one is based on Iterated Local Search; the second 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 distribution warehouses to be operated significantly more efficiently.
Subjects: 
warehouse management
order picking
order batching
iterated local search
ant colony optimization
Persistent Identifier of the first edition: 
Document Type: 
Article

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