A stochastic programming model for a tactical solid waste management problem

Claudio Gambella*, Francesca Maggioni, Daniele Vigo

*Corresponding author for this work

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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.

Original languageEnglish
Pages (from-to)684-694
Number of pages11
JournalEuropean Journal of Operational Research
Volume273
Issue number2
Early online date10 Aug 2018
DOIs
Publication statusPublished - 1 Mar 2019

Funding

Research activities of Claudio Gambella related to this paper were entirely performed at DEI, University of Bologna. Research activities of Daniele Vigo were supported by MIUR, Italy. Francesca Maggioni has been supported by Bergamo University grant, years 2015–2016. The authors gratefully thank Adriano Guarnieri, Fabrizio Salieri and Alessandro Testi of HERAmbiente SpA and Fabio Lombardi and Lorenzo Ravaglia of Optit srl for providing the data on waste generation and the waste-treatment network. Finally, the authors would like to thank Prof. Georg Pflug and Juan Ramon Trapero Arenas for useful discussions on a preliminary version of the paper.

Keywords

  • Network flow
  • OR in service industries
  • Stochastic programming
  • Waste management

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