{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T12:29:41Z","timestamp":1771504181715,"version":"3.50.1"},"reference-count":71,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Agenda Transform","award":["C644865735-00000007"],"award-info":[{"award-number":["C644865735-00000007"]}]},{"name":"Recovery and Resilience Plan","award":["02\/C05-i01\/2021"],"award-info":[{"award-number":["02\/C05-i01\/2021"]}]},{"name":"European Funds NextGeneration EU"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>The forest-to-bioenergy supply chain is significantly vulnerable to natural disruptions, including wildfires, heavy snowfall, and windstorms. The increased occurrence of these disruptive events has caused severe challenges in forest biomass harvesting and transportation processes, which are difficult to manage. With the need to support decision-makers in designing resilient supply chains (SCs), we propose a Decision Support System (DSS) combining a two-stage stochastic programming framework with various flexibility mechanisms, such as dynamic network reconfiguration and operations postponement. The DSS incorporates an AI-based methodology to identify the most appropriate datasets and resilience metrics, capturing different supply chain dimensions (supply, demand, and operations). This integrated framework supports the selection of effective resilience-enhancing strategies to mitigate large-scale disruptions, with a particular focus on wildfires. The proposed approach is applied in a real case study in Portugal, where the most significant risk factor is wildfires. We perform computational studies and sensitivity analysis to evaluate the applicability and performance of the model and to drive managerial insights. The results show that adopting the model solutions can significantly reduce supply chain logistics and operational costs under more severe disruptive scenarios. Moreover, the results indicate up to a 60% increase in the tons of forest residues that can be removed and processed.<\/jats:p>","DOI":"10.3390\/su18042086","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:44:27Z","timestamp":1771501467000},"page":"2086","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-Enabled Flexible Design of Resilient Forest-to-Bioenergy Supply Chains Under Wildfire Disruption Risk"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5352-0830","authenticated-orcid":false,"given":"Reinaldo","family":"Gomes","sequence":"first","affiliation":[{"name":"Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ci\u00eancia, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3338-295X","authenticated-orcid":false,"given":"Jo\u00e3o Pires","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"CEGIST, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-01 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7643-5816","authenticated-orcid":false,"given":"Ruxanda Godina","family":"Silva","sequence":"additional","affiliation":[{"name":"Departamento de Economia, Gest\u00e3o, Engenharia Industrial e Turismo (DEGEIT), Universidade de Aveiro, Campus Universit\u00e1rio de Santiago, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3742-7978","authenticated-orcid":false,"given":"Ricardo","family":"Soares","sequence":"additional","affiliation":[{"name":"Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ci\u00eancia, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.biombioe.2018.09.005","article-title":"An integrated sustainability model for a bioenergy system: Forest residues for electricity generation","volume":"119","author":"Jin","year":"2018","journal-title":"Biomass Bioenergy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1016\/B978-0-444-63965-3.50333-0","article-title":"A design of rural energy system by industrial symbiosis considering availability of regional resources","volume":"40","author":"Kanematsu","year":"2017","journal-title":"Comput. 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