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Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description

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  • Vadenbo, Carl
  • Hellweg, Stefanie
  • Guillén-Gosálbez, Gonzalo

Abstract

This article presents a general multi-objective mixed-integer linear programming (MILP) optimization model aimed at providing decision support for waste and resources management in industrial networks. The MILP model combines material flow analysis, process models of waste treatments and other industrial processes, life cycle assessment, and mathematical optimization techniques within a unified framework. The optimization is based on a simplified representation of industrial networks that makes use of linear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heating value or heavy metal contamination, are considered explicitly along with potential technologies or process configurations. The systems perspective, including both provision of waste treatment and industrial production, enables constraints imposed upon the systems, e.g. available treatment capacities, to be explicitly considered in the model. The model output is a set of alternative system configurations in terms of distribution of waste and resources that optimize environmental and economic performance. The MILP also enables quantification of the improvement potential compared to a given reference state. Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficient solutions. This information supports the decision making process by revealing the quantified performance of the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key features of the modeling approach are illustrated in a hypothetical case. The optimization model described in this article is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewage sludge in a region in Switzerland.

Suggested Citation

  • Vadenbo, Carl & Hellweg, Stefanie & Guillén-Gosálbez, Gonzalo, 2014. "Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description," Resources, Conservation & Recycling, Elsevier, vol. 89(C), pages 52-63.
    • Handle: RePEc:eee:recore:v:89:y:2014:i:c:p:52-63
    DOI: 10.1016/j.resconrec.2014.05.010
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    References listed on IDEAS

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    1. Meylan, Grégoire & Ami, Helen & Spoerri, Andy, 2014. "Transitions of municipal solid waste management. Part II: Hybrid life cycle assessment of Swiss glass-packaging disposal," Resources, Conservation & Recycling, Elsevier, vol. 86(C), pages 16-27.
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    7. Meylan, Grégoire & Seidl, Roman & Spoerri, Andy, 2013. "Transitions of municipal solid waste management. Part I: Scenarios of Swiss waste glass-packaging disposal," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 8-19.
    8. Tan, Raymond R. & Aviso, Kathleen B. & Barilea, Ivan U. & Culaba, Alvin B. & Cruz, Jose B., 2012. "A fuzzy multi-regional input–output optimization model for biomass production and trade under resource and footprint constraints," Applied Energy, Elsevier, vol. 90(1), pages 154-160.
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    1. Vadenbo, Carl & Guillén-Gosálbez, Gonzalo & Saner, Dominik & Hellweg, Stefanie, 2014. "Multi-objective optimization of waste and resource management in industrial networks – Part II: Model application to the treatment of sewage sludge," Resources, Conservation & Recycling, Elsevier, vol. 89(C), pages 41-51.
    2. Christine Roxanne Hung & Paul Kishimoto & Volker Krey & Anders Hammer Strømman & Guillaume Majeau‐Bettez, 2022. "ECOPT2: An adaptable life cycle assessment model for the environmentally constrained optimization of prospective technology transitions," Journal of Industrial Ecology, Yale University, vol. 26(5), pages 1616-1630, October.
    3. Klinglmair, Manfred & Vadenbo, Carl & Astrup, Thomas Fruergaard & Scheutz, Charlotte, 2017. "An MFA-based optimization model for increased resource efficiency: Phosphorus flows in Denmark," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 1-10.
    4. Nakatani, Jun & Konno, Kiyoto & Moriguchi, Yuichi, 2017. "Variability-based optimal design for robust plastic recycling systems," Resources, Conservation & Recycling, Elsevier, vol. 116(C), pages 53-60.
    5. Inghels, Dirk & Dullaert, Wout & Bloemhof, Jacqueline, 2016. "A model for improving sustainable green waste recovery," Resources, Conservation & Recycling, Elsevier, vol. 110(C), pages 61-73.
    6. Cai, Yanpeng & Yue, Wencong & Xu, Linyu & Yang, Zhifeng & Rong, Qiangqiang, 2016. "Sustainable urban water resources management considering life-cycle environmental impacts of water utilization under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 21-40.

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