Integrating order picking and delivery decisions in a dynamic setting

Abstract

The growing importance of e-commerce retail, accompanied with the need of offering a high customer service level, requires companies to optimise their operations. One possible area of improvement is the integration of order picking and delivery decisions. If a new customer order arrives, the requested items first need to be picked in the warehouse. Afterwards, the items are delivered to the customer’s location. Traditionally, the picking and delivery operations are considered individually and in a sequential manner. By using integrated decision making, however, more efficient operations can be obtained. Since customers demand very fast deliveries, the use of an online optimisation strategy is preferred, as it allows to consider new customer orders very quickly in the current operating schedule. While previous research considered the integration of picking and delivery in a static problem setting, its impact in a dynamic setting is yet unstudied. We propose new metaheuristic algorithms to solve the integrated picking and delivery problem in a dynamic setting. The performance of several algorithms, i.e., a simple sequential algorithm, an iterative algorithm and two integrated algorithms, is compared to show the benefits of using a more involved optimisation strategy.