Population growth and the acceleration of urbanization have led to a sharp increase in municipal solid waste production, and researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modeling complex nonlinear processes and have been gradually adopted to promote municipal solid waste management (MSWM) and help the sustainable development of the environment in the past few years. In this study, more than 200 publications published over the last two decades (2000–2020) were reviewed and analyzed. This paper summarizes the application of ML algorithms in the whole process of MSWM, from waste generation to collection and transportation, to final disposal. Through this comprehensive review, the gaps and future directions of ML application in MSWM are discussed, providing theoretical and practical guidance for follow-up related research.

人口增长和城市化进程的加速导致城市固体废物的产生急剧增加，研究人员试图利用先进的技术来解决这个问题。机器学习（ML）算法擅长对复杂的非线性过程进行建模，并在过去几年逐渐被用于促进城市固体废物管理（MSWM）和帮助环境的可持续发展。在这项研究中，对过去二十年（2000-2020 年）发表的 200 多篇出版物进行了审查和分析。本文总结了 ML 算法在 MSWM 整个过程中的应用，从废物产生到收集和运输，再到最终处置。通过这次全面回顾，讨论了 MSWM 中 ML 应用的差距和未来方向，