An Optimization-Based System Dynamics Simulation for Sustainable Policy Design in WEEE Management Systems

The increase in the use of electrical and electronic devices worldwide has created a rapid growth of waste of electrical and electronic equipment (WEEE). The current paper presents an optimization-based simulation (OBS) approach that allows the design of sustainable WEEE management system policies. The proposed OBS approach integrates a system dynamics (SD) model and a mixed-integer nonlinear programming (MINLP) model to improve the representation and performance of the WEEE processes considering their operative and strategic interdependence. The SD component elicits the complexity of the WEEE generation process. Complementarily, the MINLP model periodically optimizes key variables of the WEEE management system. Computational results in a case study based on WEEE from Colombian mobile phones illustrates how an approach solely based on SD simulation is unable to capture the operative-strategic nature of the system and perform optimal parameter updates. By contrast, the OBS approach of this paper outperforms an exclusive SD analysis both in the economic and environmental performance of the system. It obtains 33% more profits and 65% more environmental benefits. Moreover, for this case study, the model suggests that the cornerstone of the WEEE management system for increasing its performance is the replacement rate.

Automated summary

The paper introduces an optimization-based simulation approach for designing sustainable management system policies for Waste of Electrical and Electronic Equipment (WEEE). By integrating a system dynamics model and a mixed-integer nonlinear programming model, the proposed approach enhances the representation and performance of WEEE processes. Computational results show that the approach outperforms exclusive system dynamics analysis in both economic and environmental aspects, achieving higher profits and environmental benefits. The model suggests that the cornerstone for improving system performance in the case study is the replacement rate.