Purpose: This model aims at solving a Green Heterogeneous and Stochastic Capacitated Vehicle Routing Problem that takes into account the risks and environmental hazards.
Research Methodology: Regarding an NP-hard and complex problem, and after confirming the accuracy of the problem-solving in smaller dimensions by GAMS software, the problem is solved by the metaheuristic algorithm of multi-objective particle swarm optimization (MOPSO) and its coding in MATLAB software.
Results: The results urge that using random sampling and probability distribution, non-deterministic parameters turned into deterministic ones, and high-quality solutions were obtained.
Limitation: The proposed method is a routing problem and has been applied for the Green Heterogeneous and Stochastic Capacitated Vehicle Routing Problem. Future researchers may work on real data sets and hazardous biomedical waste data.
Contribution: Based on the results presented, the model derived in this paper can support decisions such as routing, prioritization, time to reach each node, etc. so that the costs of routing, system reliability, environmental issues, and penalties for violation of the priority and maximum time elapsed for vehicles are taken into account.