Abstract
Solid waste management poses a rich variety of interesting and challenging optimization problems. Waste managers are required to take short-, medium-, and long-term planning decisions, while taking into account the articulated multi-echelon supply chain of waste generation, treatment and disposal. In all such situations, neglecting the uncertainty of the waste generation rates can lead to unreliable decision plans. In this paper, we address a tactical problem of waste flow allocation from a waste operator point of view with the aim of minimizing the total management cost, net of possible profits obtained by special subproducts. We propose a two-stage multi-period stochastic programming formulation. The first-stage decisions take into account the facility activation and a pre-allocation of waste flow, while the recourse action considers the excess waste. We then benchmark the formulation by solving an instance derived from historical data provided by a large Italian waste treatment company. Scenario trees are generated from predictive models of unsorted waste. Finally, the impact of the stochastic waste generation on the problem solution is examined, showing the benefit of the stochastic methodology when compared with the deterministic formulation.
| Language | English |
|---|---|
| Pages | 684-694 |
| Journal | European Journal of Operational Research |
| Volume | 273 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2019 |
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Keywords
- Network flow
- OR in service industries
- Stochastic programming
- Waste management
Cite this
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A stochastic programming model for a tactical solid waste management problem. / Gambella, Claudio; Maggioni, Francesca; Vigo, Daniele.
In: European Journal of Operational Research, Vol. 273, No. 2, 2019, p. 684-694.Research output: Contribution to Journal › Article › Academic › peer-review
TY - JOUR
T1 - A stochastic programming model for a tactical solid waste management problem
AU - Gambella,Claudio
AU - Maggioni,Francesca
AU - Vigo,Daniele
PY - 2019
Y1 - 2019
N2 - Solid waste management poses a rich variety of interesting and challenging optimization problems. Waste managers are required to take short-, medium-, and long-term planning decisions, while taking into account the articulated multi-echelon supply chain of waste generation, treatment and disposal. In all such situations, neglecting the uncertainty of the waste generation rates can lead to unreliable decision plans. In this paper, we address a tactical problem of waste flow allocation from a waste operator point of view with the aim of minimizing the total management cost, net of possible profits obtained by special subproducts. We propose a two-stage multi-period stochastic programming formulation. The first-stage decisions take into account the facility activation and a pre-allocation of waste flow, while the recourse action considers the excess waste. We then benchmark the formulation by solving an instance derived from historical data provided by a large Italian waste treatment company. Scenario trees are generated from predictive models of unsorted waste. Finally, the impact of the stochastic waste generation on the problem solution is examined, showing the benefit of the stochastic methodology when compared with the deterministic formulation.
AB - Solid waste management poses a rich variety of interesting and challenging optimization problems. Waste managers are required to take short-, medium-, and long-term planning decisions, while taking into account the articulated multi-echelon supply chain of waste generation, treatment and disposal. In all such situations, neglecting the uncertainty of the waste generation rates can lead to unreliable decision plans. In this paper, we address a tactical problem of waste flow allocation from a waste operator point of view with the aim of minimizing the total management cost, net of possible profits obtained by special subproducts. We propose a two-stage multi-period stochastic programming formulation. The first-stage decisions take into account the facility activation and a pre-allocation of waste flow, while the recourse action considers the excess waste. We then benchmark the formulation by solving an instance derived from historical data provided by a large Italian waste treatment company. Scenario trees are generated from predictive models of unsorted waste. Finally, the impact of the stochastic waste generation on the problem solution is examined, showing the benefit of the stochastic methodology when compared with the deterministic formulation.
KW - Network flow
KW - OR in service industries
KW - Stochastic programming
KW - Waste management
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UR - http://www.scopus.com/inward/citedby.url?scp=85052310909&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2018.08.005
DO - 10.1016/j.ejor.2018.08.005
M3 - Article
VL - 273
SP - 684
EP - 694
JO - European Journal of Operational Research
T2 - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 2
ER -