Biogas Reverse Supply Chain Network Design based on Biomass Quality Levels using Robust Programming and Benders decomposition approach

Document Type : Article


Department of Industrial Engineering, Payame Noor University, Tehran. Iran


Today, renewable energy generation infrastructures are increasingly developed due to reduced fossil fuel resources and increased energy consumption. A biogas supply chain has a high potential to generate energy. This paper aims to design a bi-objective biogas supply chain network for power and fertilizer generation. A mixed-integer linear programming (MILP) model was developed for the multi-level biogas supply chain with biomass input under different parameter uncertainties. To cope with the intrinsic uncertainties of such value chains, a stochastic-robust programming approach was adopted. Realistic uncertainty modeling allowed for adjusting the conservatism level for a trade-off between performance and robustness. The adopted stochastic-robust programming pathway not only diminished the optimality fluctuations and provided a reasonable allocation space for uncertainties but also enhanced network flexibility and alleviated decision-making risks. Finally, the model was solved using the Benders decomposition(BD) algorithm. Drawing on previously generated solutions and Pareto optimal cuts, Benders cuts were enhanced, leading to more efficient and effective solutions. The implemented algorithm converged to the optimal solution at a reasonable rate.


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