Towards sustainable forest management strategies with MOEAs

Philipp Back*, Antti Suominen, Pekka Malo, Olli Tahvonen, Julian Blank, Kalyanmoy Deb

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

Sustainable forest management is a crucial element in combating climate change, plastic pollution, and other unsolved challenges of the 21st century. Forests not only produce wood - a renewable resource that is increasingly replacing fossil-based materials - but also preserve biodiversity and store massive amounts of carbon. Thus, a truly optimal forest policy has to balance profit-oriented logging with ecological and societal interests, and should thus be solved as a multi-objective optimization problem. Economic forest research, however, has largely focused on profit maximization. Recent publications still scalarize the problem a priori by assigning weights to objectives. In this paper, we formulate a multi-objective forest management problem where profit, carbon storage, and biodiversity are maximized. We obtain Pareto-efficient forest management strategies by utilizing three state-of-the-art Multi-Objective Evolutionary Algorithms (MOEAs), and by incorporating domain-specific knowledge through customized evolutionary operators. An analysis of Pareto-efficient strategies and their harvesting schedules in the design space clearly shows the benefits of the proposed approach. Unlike many EMO application studies, we demonstrate how a systematic post-optimality trade-off analysis can be applied to choose a single preferred solution. Our pioneering work on sustainable forest management explores an entirely new application area for MOEAs with great societal impact.
AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2020 Genetic and Evolutionary Computation Conference
KustantajaACM
Sivut1046-1054
ISBN (painettu)9781450371285
DOI - pysyväislinkit
TilaJulkaistu - 25 kesäkuuta 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaGenetic and Evolutionary Computation Conference - Cancun, Meksiko
Kesto: 8 heinäkuuta 202012 heinäkuuta 2020

Conference

ConferenceGenetic and Evolutionary Computation Conference
LyhennettäGECCO
MaaMeksiko
KaupunkiCancun
Ajanjakso08/07/202012/07/2020

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  • Siteeraa tätä

    Back, P., Suominen, A., Malo, P., Tahvonen, O., Blank, J., & Deb, K. (2020). Towards sustainable forest management strategies with MOEAs. teoksessa Proceedings of the 2020 Genetic and Evolutionary Computation Conference (Sivut 1046-1054). ACM. https://doi.org/10.1145/3377930.3389837