In-store order fulfilment in omni-channel supermarkets with heterogeneous workforce: A bi-objective optimisation approach

Abstract

The development of omni-channel retailing brings both opportunities and challenges to conventional supermarkets. Utilising local establishments to complete online customer orders is critical to providing timely and seamless omni-channel shopping experiences. We propose a bi-objective mixed-integer non-linear order batching and assignment optimisation model with the objectives of minimising person-hours, earliness and tardiness penalties, and workload imbalance. We apply a multi-objective genetic algorithm-based heuristic to obtain the Pareto frontier solutions in an omni-channel supermarket case, demonstrating the effectiveness of the proposed model and trade-offs among objectives. By conducting extensive numerical experiments, we discuss the influences of unique operational attributes in omni-channel supermarkets, namely workforce heterogeneity and store crowding, on the performance of in-store order fulfilment. Results suggest that the proposed model are relatively robust to workforce heterogeneity and coordinating online/offline channel traffic in peak hours is of importance. Overall, the research highlights the essence of bi-objective optimisation in order fulfilment and the importance of incorporating the operational attributes in omni-channel retail stores. We lastly provide managerial insights for in-store order fulfilment in omni-channel supermarkets.