Circular economy imposes a new view of operations with the aim of zero waste. To obtain this result it is critical to adopt an holistic approach and to optimize every step of the production and logistics processes. 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, uncertainties in supplies, and difficulties to track flows. In these settings, we propose a mixed integer linear programming model to schedule the sorting operations of each phase of the waste sorting process. The model can be described as a variant of a lot size model with non linear costs (approximated by mean of piece-wise linear functions) with the additional features of scheduling the operations and allocating the appropriate workforce dimension. The model is tested on a real world case study and results demonstrate the validity of the approach.
Optimal planning of waste sorting operations through mixed integer linear programming / Pinto, D. M.; Stecca, G.. - (2021), pp. 307-320. - AIRO SPRINGER SERIES. [10.1007/978-3-030-63072-0_24].
Optimal planning of waste sorting operations through mixed integer linear programming
Pinto D. M.Primo
;
2021
Abstract
Circular economy imposes a new view of operations with the aim of zero waste. To obtain this result it is critical to adopt an holistic approach and to optimize every step of the production and logistics processes. 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, uncertainties in supplies, and difficulties to track flows. In these settings, we propose a mixed integer linear programming model to schedule the sorting operations of each phase of the waste sorting process. The model can be described as a variant of a lot size model with non linear costs (approximated by mean of piece-wise linear functions) with the additional features of scheduling the operations and allocating the appropriate workforce dimension. The model is tested on a real world case study and results demonstrate the validity of the approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.