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Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix: A Methodical Approach

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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)

Abstract

Background: In the pursuit of sustainable energy sources, residual biomass has emerged as a promising renewable resource. However, efficiently managing residual biomass poses significant challenges, particularly in optimizing supply chain operations. Advanced modeling approaches are necessary to address these complexities. This study aims to develop a comprehensive methodological framework for creating simulation models tailored to agroforestry residual biomass supply chains. Methods: The study employs a hybrid simulation approach, integrating geographic information system mapping with a case study analysis. The simulation was conducted over a 365-day period, using the anyLogistix software (version 2.15.3.202209061204) to model various supply chain dynamics. The framework also accounts for financial, operational, customer satisfaction, and environmental metrics. Results: The simulation results showed a total expenditure of EUR 5,219,411.3, with transportation being the primary cost driver, involving 5678 trips and a peak capacity of 67.16 m 3 . CO 2 emissions were measured at 487.7 kg/m 3 . The model performed as expected, highlighting the need for sustainable logistics strategies to reduce costs, lower losses, and improve productivity. Conclusions: This study presents one of the first detailed methodological frameworks for simulating agroforestry residual biomass supply chains. It provides valuable managerial insights into the financial, operational, and environmental aspects of supply chain management. The findings may stakeholders make informed decisions to enhance the sustainability of biomass utilization in energy production.

Suggested Citation

  • Bernardine Chidozie & Ana Ramos & José Vasconcelos & Luis Pinto Ferreira, 2024. "Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix: A Methodical Approach," Logistics, MDPI, vol. 8(4), pages 1-18, October.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:4:p:107-:d:1501947
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    References listed on IDEAS

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    1. Tiago Bastos & Leonor C. Teixeira & João C. O. Matias & Leonel J. R. Nunes, 2023. "Agroforestry Biomass Recovery Supply Chain Management: A More Efficient Information Flow Model Based on a Web Platform," Logistics, MDPI, vol. 7(3), pages 1-15, August.
    2. Aalto, Mika & KC, Raghu & Korpinen, Olli-Jussi & Karttunen, Kalle & Ranta, Tapio, 2019. "Modeling of biomass supply system by combining computational methods – A review article," Applied Energy, Elsevier, vol. 243(C), pages 145-154.
    3. Leonel J. R. Nunes & Sandra Silva, 2023. "Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis," Logistics, MDPI, vol. 7(3), pages 1-21, August.
    4. Zailan, Roziah & Lim, Jeng Shiun & Manan, Zainuddin Abdul & Alwi, Sharifah Rafidah Wan & Mohammadi-ivatloo, Behnam & Jamaluddin, Khairulnadzmi, 2021. "Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    5. Vitale, Ignacio & Dondo, Rodolfo G. & González, Matías & Cóccola, Mariana E., 2022. "Modelling and optimization of material flows in the wood pellet supply chain," Applied Energy, Elsevier, vol. 313(C).
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