{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T23:56:28Z","timestamp":1715644588673},"edition-number":"1.\u00aa Edi\u00e7\u00e3o","reference-count":0,"publisher":"Imprensa da Universidade de Coimbra","isbn-type":[{"value":"9789892622989","type":"electronic"},{"value":"9789892622972","type":"print"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"abstract":"<jats:p>We propose a method for forest management in which wildfire is modeled explicitly through the integration of optimisation and simulation. Given a forest, the decision problem is to select a plan (i.e. a prescription and a periodicity for brush cleaning) for each of its stands. Each plan is associated with values for a set of criteria for each period of the temporal horizon. Considered criteria are net present value, biodiversity, carbon stock, and erosion. The problem is modelled by a mixed integer programming (MIP) with the objective of maximizing the net present value and imposing limits for the remaining criteria. A fire spread simulator, based on shortest path algorithms following the minimum travel time principle, is responsible to identify sets of plans that are not acceptable together as they result in a high rate of fire spread. That information is included in the MIP as constraints. This cycle optimization-simulation is repeated until the plans provided by the MIP are acceptable in all scenarios. Data from a real landscape case-study has been collected and processed to obtain management and fire parameters required to validate the proposed method, which is being implemented in Python (with Gurobi as a MIP solver, GeoPandas for managing and processing geospatial data, and NetworkX implementation of graph algorithms).<\/jats:p>","DOI":"10.14195\/978-989-26-2298-9_49","type":"book-chapter","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T22:29:39Z","timestamp":1666823379000},"page":"309-314","source":"Crossref","is-referenced-by-count":0,"title":["Optimization with fire spread simulation for forest management"],"prefix":"10.14195","author":[{"given":"Filipe","family":"Alvelos","sequence":"first","affiliation":[]},{"given":"Isabel","family":"Martins","sequence":"additional","affiliation":[]},{"given":"Susete","family":"Marques","sequence":"additional","affiliation":[]},{"given":"Mariana","family":"Dias","sequence":"additional","affiliation":[]},{"given":"Eduardo","family":"Cunha","sequence":"additional","affiliation":[]},{"given":"David","family":"Neto","sequence":"additional","affiliation":[]}],"member":"5739","container-title":["Advances in Forest Fire Research 2022"],"original-title":[],"language":"pt","deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T09:18:26Z","timestamp":1698052706000},"score":1,"resource":{"primary":{"URL":"http:\/\/books.uc.pt\/chapter?chapter=978989262298949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789892622989","9789892622972"],"references-count":0,"URL":"https:\/\/doi.org\/10.14195\/978-989-26-2298-9_49","relation":{},"subject":[],"published":{"date-parts":[[2022]]}}}