The booming development of e-commerce has brought many challenges to the logistics industry. To ensure the sustainability of the logistics industry, the impact of environmental and social sustainability factors on logistics development needs to be considered. Unmanned Aerial Vehicles (UAVs)/drones are used in the logistics field because of their flexibility, low cost, environmental protection and energy-saving advantages, which can achieve both economic benefits and social benefits. This paper reviews 36 studies on UAVs applications in logistics from the Web of Science database from the past two years (2021–2022). The selected literature is classified into theoretical models (the traveling salesman problem and other path planning problems), application scenarios (medical safety applications and last-mile delivery problems) and other problems (UAV implementation obstacles, costs, pricing, etc.). Finally, future directions of UAVs are proposed, such as different application scenarios that can be considered and different algorithms that can be combined to optimize paths for UAVs to specific flight environments.

With the vigorous development of e-commerce, efficient order picking in e-commerce warehouses has attracted the attention of many scholars. To analyze the issues about order-picking efficiency currently being studied by relevant scholars in e-commerce warehouses, this paper reviews the literature on the application of order-picking strategy and efficiency optimization direction from 2020 to 2022. That mainly falls into two categories of picking systems: “picker-to-parts” and “parts-to-picker”. In the “picker-to-parts” picking system, more attention is paid to the picking strategies of storage assignment and order batching and the integration of multiple picking strategies. In contrast, in the “parts-to-picker” picking system, the main attention is on the man-machine cooperation in the Mobile Robot Fulfillment System (RMFS) and the Automated Storage and Retrieval System (AS/RS), as well as the coordination of the picking station. Further, this paper proposes future research directions for two categories of picking systems: further studying the order splitting strategy and order delivery issues; considering the dynamic uncertainties; combining the automated picking system with different picking strategies, and so on.