The valorization of brownfields presents a significant challenge in urban redevelopment, as decisions in this domain involve a trade-o; between environmental sustainability and financial feasibility. Our study, focusing on three sites in Switzerland, introduces a comprehensive
decision-support system (DSS) that integrates operations research methodologies to optimize the rehabilitation process of such sites. Within this DSS, we identify key cost
components related to material transport and rehabilitation expenses, including routing, vehicle usage, tools, materials, storage, transformation/repackaging, and recycling costs. Our DSS finds the most efficient strategy while considering (i) spatial constraints, i.e., the locations of brownfield sites, storage sites, recycling centers, transformation/repackaging facilities, and construction sites; (ii) technical constraints, i.e., facility and vehicle
capacities and material-related restrictions; and (iii) financial constraints, i.e., budget limitations. By developing a mixed-integer linear programming model, we aim to provide the optimal assignment of materials between sites and the vehicle routing of material transport. The results of this research are planned to be integrated into a brownfield rehabilitation framework that benefits from circular economy practices in construction, proposing incentives to promote sustainability.
