Techno-economic impact analysis of solid waste collection optimization and management for smart city towards achieving sustainable development goals

Solid waste collection optimization plays a critical role in advancing sustainable urban waste management, particularly in the context of smart cities. Traditional collection methods relying on fixed schedules and routes have led to inefficiencies such as excessive operational costs, increased carbon emissions, and inadequate waste segregation. This review examines the latest advancements in optimization techniques for solid waste collection, including mathematical modeling, heuristic and metaheuristic algorithms, artificial intelligence (AI), geographic information systems (GIS), and Internet of Things (IoT)-based smart waste management. The study highlights the techno-economic impact of these approaches, assessing cost savings, resource efficiency, and environmental benefits. Additionally, the paper identifies key challenges in implementation, such as financial constraints, infrastructure limitations, and policy gaps. By integrating innovative technologies and optimization strategies, cities can enhance waste collection efficiency, reduce environmental impact, and align with sustainable development goals (SDGs). Future research should focus on hybrid optimization models, real-time data integration, and policy frameworks to facilitate large-scale adoption of smart cities waste management solutions.