Vehicle routing problem for omnichannel retailing including multiple types of time windows and products

Abstract

This paper addresses the capacitated vehicle routing problem for omnichannel retailing with multiple types of time windows (hard time windows and soft time windows) and multiple types of products simultaneously. The problem aims to transfer multiple products from a central warehouse to stores and satellites, where split delivery is allowed since the demands of stores or satellites are large and the different product types have different volumes. Based on different characteristics of purchasing channels, the time window of a store is a hard constraint while the time window of a satellite is a soft one. This type of vehicle routing problem exists extensively in omnichannel retail distribution systems in the logistics industry of China, which considers multiple purchasing channels for customers. Since this type of vehicle routing problem is an NP-hard problem and more complicated than the conventional vehicle routing problem with time windows, we design an adaptive large neighborhood search (ALNS) method to solve it. Finally, numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm and reveal some managerial insights. The numerical experiments show that the proposed algorithm can obtain a high-quality solution under a shorter computation time compared with the state-of-the-art MIP solver (Gurobi).