Ever-growing globalization and industrialization put forward impending requirements for green and sustainable logistics (G&SL). Over the past decades, G&SL initiatives triggered worldwide deliberations, aiming at easing negative transport externalities and improving supply chain performance. This review-based paper attempts to offer a joint quantitative and qualitative understanding for the overall evolutionary trend, knowledge structure, and literature gaps of the G&SL research field. Employing the science mapping approach, a total of 306 major paper published from 1999 to 2019 were retrieved, elaborated on, and synthesized. Visualized statistics regarding publication years, journal allocation/co-citation, inter-country/institution collaboration, influential articles, co-occurred keywords, and time view clusters of research themes were analyzed bibliographically. On this basis, a total of 50 sub-branches of G&SL knowledge were classified and thematically discussed based on five alignments, namely (i) social-environmental-economic research, (ii) planning, policy and management, (iii) application and practice, (iv) technology, and (v) operations research. Finally, the current knowledge obstacles and the future research opportunities were suggested. The findings contribute to portray a systematic intellectual prospect for the state quo, hotspots, and academic frontiers of G&SL research. Moreover, it provides researchers and practitioners with heuristic thoughts to govern transportation ecology and logistics service quality.

The challenges arising from the management of municipal solid waste (MSW) have a profound impact on the sustainable development of urban areas. As a sustainable solution, the transportation of MSW underground offers the potential to alleviate traffic congestion and reduce environmental pollution. In this study, we propose the implementation of a large-scale underground waste collection system (UWCS). To begin, a comprehensive operational process for the UWCS is designed based on an intelligent technology system, including facility operation, processing workflow, and technical parameters. Additionally, network planning methods for the UWCS are presented. A mixed-integer linear programming model is formulated with the objective of minimizing total cost. This model determines the optimal location and allocation of nodes within the network, as well as the pipeline layout and flow direction. Given the computational complexity, a hybrid optimization method, namely the genetic greedy algorithms and genetic variable neighborhood search algorithms (GGA-GVNS), is devised to obtain high-quality solutions for the model. Finally, to validate the efficacy of the proposed method, a simulation is conducted in the central city of Nanjing, China. The results demonstrate that the implementation of the UWCS network in Nanjing’s city center can yield an annual benefit of USD 5.99 million. Moreover, a sensitivity analysis reveals further MSW management-related insights and long-term planning strategies.