A Stochastic Programming Approach for the Design of Multi-Storey Recycling Facility

A rapid increase in urban population creates major challenges related to urban sprawl, pollution and waste generation, unsustainable production and consumption patterns. These challenges become even more crucial in the case of land-constrained urban territories, such as Singapore and Hong Kong, and require the development of decision-making methodologies for flexible long-term land use planning. The paper explores the possible relocation of decentralized companies with similar work processes to relocate towards centralized Multi-Storey Factories (MSF) for a higher density of land use. The developed decision-making methodologies aim, on the one hand, to maximize land savings and, on the other hand, to decrease each company's operational budget evaluated under uncertainties in future operational conditions, such as transportation costs. The optimization problem addressed has been formulated as a two-stage stochastic problem and tested for the application case of Multi-Storey Recycling Facility (MSRF). Optimization under uncertainty shows a 16.46% increase in estimated land savings in comparison with the solution obtained under deterministic conditions.