This paper focuses on the challenges of urban waste sorting and transportation scheduling, establishing a mathematical modelling and optimisation framework that integrates vehicle path planning, multi-vehicle collaborative scheduling, and facility location optimisation. The study first establishes a CVRP model for single-vehicle route optimisation, employing an improved heuristic algorithm (combining PathCheapestArc and the 2-opt operator) to achieve efficient solutions. Next, in multi-vehicle scheduling, the traditional model is expanded to incorporate constraints such as time windows, with a solver used to perform collaborative optimisation. Finally, a two-stage decomposition method is proposed for transfer station site selection and carbon emissions optimisation. using clustering analysis and the P-median model to make the first-stage location decisions, and then embedding carbon emission targets into the second-stage route optimisation. This study innovatively proposes an integrated optimisation framework, designs a hybrid solution method combining precise algorithms and heuristic strategies, and for the first time systematically incorporates carbon emission indicators into transportation scheduling models, providing a scientific decision-support tool for urban waste classification management.
Sun et al. (Tue,) studied this question.