Garbage collection is an important issue in urban environmental management.With the increased awareness of urban residents regarding safety,environmental protection,and health in recent years,it is necessary to logically organize municipal solid waste collection and transportation routes while also considering economic and social benefits.This article focuses on the optimization of the waste transportation routes of garbage trucks.With the objective of minimizing transportation costs and maximizing resident satisfaction,we establish a robust optimization model for the multi-trip collection and transportation of municipal solid waste in an uncertain environment.Resident satisfaction is defined as the penalty cost against a time window constraint.The Bertsimas robust optimization method is applied to characterize the uncertainty,and the decision-making scheme of the receiving route is used to adapt to waste volume changes.We conduct a case study based on real-world data for municipal solid waste collection and transportation in the Dongcheng District of Beijing,China.The solution is validated using the CPLEX program,and the validity of the model is verified.In addition,a sensitivity analysis of related parameters is conducted to study the impacts of variations in work hour limits and time windows on the total cost and service levels,as well as their relationships with the level of robustness.This could help decision-makers make reasonable choices based on actual conditions and to balance reductions in total cost with service level improvements.