A rule-based heuristic algorithm for on-line order batching and scheduling in an order picking warehouse with multiple pickers

Abstract

In manual order picking systems, orders received from internal or external customers are collected by pickers that walk or ride through the warehouse. Generally, orders are grouped into several sub sets, i.e. batches to reduce picking time and cost. This paper considers the on-line order batching problem (OOBP) in an order picking warehouse with multiple pickers in which the maximum completion time of all batches (customer orders) has to be minimized. At first, a mathematical model is introduced for the off-line version of the problem. Then the on-line version of the problem is considered in which customer orders become available dynamically over time. Since the proposed model is NP-hard, a rule-based heuristic algorithm was proposed to solve the on-line problem. The main contributions of the present work is to propose a mathematical model for the off-line order batching problem with multiple pickers considering makespan minimization and to present a novel heuristic algorithm for solving the on-line version of the problem. To validate the proposed algorithm, it is proved that its competitive rate is equal to 2. Finally, the solution algorithm is evaluated through a series of experiments and the most appropriate routing, batching and selection policies are introduced.