Henn, Sebastian Koch, Sören Doerner, Karl F. Strauss, Christine Wäscher, Gerhard
Year of Publication:
[Journal:] BuR - Business Research [ISSN:] 1866-8658 [Volume:] 3 [Issue:] 1 [Publisher:] VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research [Place:] Göttingen [Year:] 2010 [Pages:] 82-105
VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research, Göttingen
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.
warehouse management order picking order batching iterated local search ant colony optimization