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Stochastic Optimization Approaches to Biomass-to-Bioenergy Supply Chain Network Design Under Demand Uncertainty

Author

Listed:
  • Omid Mohagheghi

    (Concordia University)

  • Shiva Rezvani

    (Kharazmi University)

  • Erfan Hassannayebi

    (Sharif University of Technology)

Abstract

A critical part of the bioenergy production process is the robust design of the supply chain network. This research proposes robust optimization programming models to design a supply chain network that generates electricity from renewable energy sources under demand uncertainty. The objective is to design a biomass supply chain network that maximizes the profit of a power plant. Given the uncertain electricity demand, a two-stage stochastic programming model is proposed. A hybrid of risk-neutral and risk-averse modeling frameworks is proposed to analyze the alternative biomass-to-bioenergy supply chain design scenarios. The mathematical model has been proven to be effective in justifying the supply chain design based on a case study of the biomass-to-bioenergy supply chain in Iran. The research findings show that the proposed stochastic programming approach outperforms the conventional optimization approaches in terms of solution robustness.

Suggested Citation

  • Omid Mohagheghi & Shiva Rezvani & Erfan Hassannayebi, 2025. "Stochastic Optimization Approaches to Biomass-to-Bioenergy Supply Chain Network Design Under Demand Uncertainty," SN Operations Research Forum, Springer, vol. 6(3), pages 1-25, September.
    • Handle: RePEc:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00516-y
    DOI: 10.1007/s43069-025-00516-y
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    References listed on IDEAS

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