Citation: Piqueiro, H.; Gomes, R.; Santos, R.; de Sousa, J.P. Managing Disruptions in a Biomass Supply Chain: A Decision Support System Based on Simulation/Optimisation. Sustainability 2023, 15, 7650. https:// doi.org/10.3390/su15097650 Academic Editor: Jurgita Antucheviˇ cien ˙ e Received: 12 March 2023 Revised: 2 May 2023 Accepted: 3 May 2023 Published: 6 May 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). sustainability Article Managing Disruptions in a Biomass Supply Chain: A Decision Support System Based on Simulation/Optimisation Henrique Piqueiro 1, * , Reinaldo Gomes 1,2 , Romão Santos 1 and Jorge Pinho de Sousa 1,2 1 INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal 2 Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal * Correspondence: henrique.piqueiro@inesctec.pt 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 1. Introduction The performance of a biomass supply chain (SC) heavily depends on its design and on how operations are planned, as higher levels of coordination and optimisation are required to maximise efficiency [1,2]. With sustainable and clean energy production capabilities, biomass energy can play, in the near future, a crucial role as a promising alternative to fossil fuels. Given abundant raw materials, ease of storage, and the potential for global production, the biomass industry is experiencing a significant growth, but there is still room for improvement in terms of profitability [3,4]. Efficient supply chain management is vital to reduce costs, to adapt to unexpected events, and to ensure demand fulfilment. Transportation and transformation of the wood into smaller particles (“chipping”) encompass a significant portion of the biomass supply chain costs [5]. Identifying operational sites, capacities and routes, as well as performing the right assignment of operations, is crucial to reduce forest biomass logistic costs and to face disruptive events, thus rendering supply chains more resilient [6]. In addition to its moisture content and low bulk density, the unique characteristics of forest biomass, such as availability and susceptibility to weather variability, make the design and management of these supply chains more complex and challenging [7,8]. Biomass is a renewable energy source derived from various organic materials, such as agricultural residues from trimming and harvestings, garden residues, and forest remains resulting from the timber industry, silvicultural operations, and wildfires [9,10]. All these forest residues can be harvested in multiple forms as logs, slabs of wood or already in Sustainability 2023, 15, 7650. https://doi.org/10.3390/su15097650 https://www.mdpi.com/journal/sustainability