Robust Optimal Planning of Waste Sorting Operations

Waste management and circular economy objectives are worthwhile and worldwide challenges concerning both the protection of the environment and the conservation of natural resources with aim of zero waste. A considerable attention has been directed over the last decade towards the optimization of planning procedures related to waste management in order to empower circular economy ambition. This work investigates the operations of waste recycling centers where materials are collected by a fleet of trucks and then sorted in order to be converted in secondary raw materials. The activity is characterized by low margins, difficulties to track flows and uncertainties in supplies. In a previous work by Pinto and Stecca a formulation has been proposed to address and optimize the sorting process. However, special attention should be paid to the fact that waste streams processes are affected by several uncertainties, such as the stochastic processes regarding waste arrivals to sorting facilities. This work extends the above mentioned formulation by introducing robustness to data uncertainties related to waste supplies. Accordingly, the main aim of this study is to develop a mixed integer linear programming model for planning and scheduling the packaging waste recycling operations taking into consideration also the stochastic nature of waste arrivals. This is done by introducing a protection function in each constraint according to the probabilistic robust approach presented in (Bertsimas and Sim, Oper Res 52(1):35–53, 2004). This approach ensures deterministic and probabilistic guarantees on constraints satisfaction. The model supports other strategic decisions such as sizing of the amount of processed waste and allocation of the optimal number of operators for each shift of the waste sorting processes. Experiments are performed on instances taken from a real case scenario in Italy and comparisons are made against different planning strategies.