One of the most challenging problems in last mile logistics (LML) has been the strategic delivery due to various market risks and opportunities. This paper provides a systematic review of LML-related studies to find current issues and future opportunities for the LML service industry. To that end, 169 works were selected as target studies for in-depth analysis of recent LML advances. First, text mining analysis was performed to effectively understand the underlying LML themes in the target studies. Then, the novel definition and typology of LML delivery services were suggested. Finally, this paper proposed the next generation of LML research through advanced delivery technique-based LML services, environmentally sustainable LML systems, improvement of LML operations in real industries, effective management of uncertainties in LML, and LML delivery services for decentralized manufacturing services. We believe that this systematic literature review can serve as a useful tool for LML decision makers and stakeholders.

To resolve challenges arising from traditional truck-based delivery systems, the integration of autonomous robots into last-mile delivery operations has recently received attention as a promising solution. This study addresses a hybrid truck-robots last-mile delivery system that encompasses both homogeneous and heterogeneous robots. To discuss battery management strategies for robots returning after rendezvousing with a truck, we propose mixed-integer linear programming models offering two options: battery recharging and battery swapping. We explore optimal solutions for truck and robot routes, as well as various robot combinations aimed at minimizing total delivery time. Additionally, we present a three-phased iterative heuristic algorithm designed to effectively solve large-sized problems. The proposed models are validated with application to Southern District, Ulsan, in the Republic of Korea, and Rapid City, South Dakota, in the U.S., serving as examples of urban and rural areas, respectively. Our findings demonstrate that the proposed truck-robots system, particularly with the battery-swapping option, can achieve up to a 50% reduction in total delivery time compared with traditional truck-only delivery systems, applicable to both urban and rural areas. Furthermore, our results underscore the importance of long driving range for the robots in urban areas for enhancing delivery system performance. We also conduct a sensitivity analysis to examine the impact of the following factors on delivery system performance: customer node size, robot speed, number of robots, and various robot ratios. This study helps fill the gap in the literature concerning hybrid truck-robot delivery systems, with implications for improving delivery efficiency and reducing total delivery time in urban areas.