Highlighting Sustainability Criteria in Residual Biomass Supply Chains: A Dynamic Simulation Approach

Bernardine Chidozie (), Ana Ramos, José Vasconcelos, Luis Pinto Ferreira and Reinaldo Gomes
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Bernardine Chidozie: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
Ana Ramos: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
José Vasconcelos: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
Luis Pinto Ferreira: School of Engineering, Polytechnic of Porto (ISEP), Rua Dr. António Bernardino de Almeida, Associate Laboratory for Energy, Transports and Aerospace (LAETA-INEGI), 4200-465 Porto, Portugal
Reinaldo Gomes: INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

Sustainability, 2024, vol. 16, issue 22, 1-24

Abstract: As environmental sustainability gains importance, enhancing supply chains to minimize environmental hazards is essential, particularly in industries using residual biomass. This study tackles this by investigating the integration of sustainability criteria into supply chain optimization for a biomass energy company in Portugal, using a combination of simulation modeling through anyLogistix software (version: 2.15.3.202209061204) and multi-criteria decision-making. Four supply chain scenarios were designed and simulated, differing in their number of distribution centers, the adoption of green logistics, and split-by-ratio distribution strategies over a 305-day period. Through the weighted sum model, Scenario C emerged as the optimal configuration, achieving a balance between operational efficiency and sustainability by reducing CO 2 emissions by up to 90% and lowering transportation costs without compromising revenue. Sensitivity analysis further highlighted the trade-offs between cost efficiency, lead times, and environmental impact, showing that the strategic placement of distribution centers and the use of eco-friendly vehicles significantly improve the sustainability of the biomass supply chain. These findings provide practical insights for decision-makers, demonstrating how digital modeling tools can enhance supply chain management by optimizing environmental and operational goals simultaneously. This research contributes to the fields of sustainable logistics and supply chain management by validating the effectiveness of green logistics strategies and multi-criteria decision-making approaches in reducing environmental impact while maintaining economic viability.

Keywords: digital twin; supply chain; residual biomass; anyLogistix; sustainability criteria; simulation; multi-criterion decision-making; optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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