Dynamic Routing of Multiple Pickers in Dark Stores and Urban Warehouses

With the current trends towards ever faster fulfilment and deliveries (i.e., e-commerce) and the need for ever more predictable fulfilment and delivery times for better synchronisation, there has been more pressure on efficient management of warehouses. The resulting demand for increased warehouse space, along with the need for social distancing, has meant that many retailers have converted locations into dark stores and urban micro-fulfilment centres. These new types of warehouses operate in an environment where the order pattern is dynamic and lead time requirements are very stringent.

In collaboration with an industrial partner developing innovative Internet-of-Things technologies and platforms for smart warehousing, we consider a warehouse setting with multiple pickers and dynamic order arrivals in this study. Given the need to address decisions in short timescales and the complexities of the orders associated with urban fulfilment, we propose a heuristic approach that extends those designed for single-picker environment by decomposing the problem into the batching, pick list updating, picker assignment, and re-routing decisions. We present our initial results using computational experiments on randomly generated instances to assess the quality of our solutions, derive managerial insights and perform sensitivity analyses.