Managing Disruptions in a Biomass Supply Chain: A Decision Support System Based on Simulation/Optimisation

Henrique Piqueiro (), Reinaldo Gomes, Romão Santos and Jorge Pinho de Sousa
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Henrique Piqueiro: INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Rua Dr. Roberto Frias, 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
Romão Santos: INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
Jorge Pinho de Sousa: INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

Sustainability, 2023, vol. 15, issue 9, 1-25

Abstract: To design and deploy their supply chains, companies must naturally take quite different decisions, some being strategic or tactical, and others of an operational nature. This work resulted in a decision support system for optimising a biomass supply chain in Portugal, allowing a more efficient operations management, and enhancing the design process. Uncertainty and variability in the biomass supply chain is a critical issue that needs to be considered in the production planning of bioenergy plants. A simulation/optimisation framework was developed to support decision-making, by combining plans generated by a resource allocation optimisation model with the simulation of disruptive wildfire scenarios in the forest biomass supply chain. Different scenarios have been generated to address uncertainty and variability in the quantity and quality of raw materials in the different supply nodes. Computational results show that this simulation/optimisation approach can have a significant impact in the operations efficiency, particularly when disruptions occur closer to the end of the planning horizon. The approach seems to be easily scalable and easy to extend to other sectors.

Keywords: decision support systems; biomass supply chain; supply chains; disruptive events; simulation/optimisation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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