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

Omid Mohagheghi (), Shiva Rezvani () and Erfan Hassannayebi ()
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Omid Mohagheghi: Concordia University
Shiva Rezvani: Kharazmi University
Erfan Hassannayebi: Sharif University of Technology

SN Operations Research Forum, 2025, vol. 6, issue 3, 1-25

Abstract: 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.

Keywords: Stochastic optimization; Biomass-to-bioenergy supply chain; Hybrid approach; Uncertainty; Risk-neutral; Risk-averse (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s43069-025-00516-y

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