Minimizing total tardiness on one machine is NP-hard
Mathematics of Operations Research
Order-batching methods for an order-picking warehouse with two cross aisles
Computers and Industrial Engineering
Batching orders in warehouses by minimizing travel distance with genetic algorithms
Computers in Industry - Special issue: Application of genetics algorithms in industry
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Order picking involves the retrieval of articles from their storage locations in order to satisfy customer requests. A major issue in manual order picking systems is the transformation and consolidation of customer orders into picking orders (order batching). In practice, customer orders have to be completed by certain due dates in order to avoid shipment or production delays. The composition of the picking orders, their processing times and the sequence according to which they are released have a significant impact on whether and to which extent due dates are violated. This paper presents how metaheuristics can be used in order to minimize the total tardiness for a given set of customer orders. The first heuristic is based on Iterated Local Search, the second is inspired by the Attribute-Based Hill Climber, a heuristic based on a simple tabu search principle. In a series of extensive numerical experiments, the performance of these metaheuristics is analyzed for different classes of instances. We will show that the proposed methods provide solutions which may allow order picking systems to operate more efficiently. Solutions can be improved by 46% on average, compared to those obtained with standard constructive heuristics such as the Earliest Due Date rule.