Interactive decision support and trade-off analysis for sustainable forest landscape planning under deep uncertainty
Shavazipour, B., Podkopaev, D., & Miettinen, K. (2022). Interactive decision support and trade-off analysis for sustainable forest landscape planning under deep uncertainty. Canadian Journal of Forest Research, 52(11), 1423-1438. https://doi.org/10.1139/cjfr-2022-0084
Julkaistu sarjassa
Canadian Journal of Forest ResearchPäivämäärä
2022Oppiaine
Laskennallinen tiedeMultiobjective Optimization GroupPäätöksen teko monitavoitteisestiComputational ScienceMultiobjective Optimization GroupDecision analytics utilizing causal models and multiobjective optimizationTekijänoikeudet
© Authors, 2022
Sustainable environmental management often involves long-term time horizons, multiple conflicting objectives, and by nature, is affected by different sources of uncertainty. Many sources of uncertainty, such as climate change or government policies, cannot be addressed using probabilistic models, and, therefore, they can be seen to contain deep uncertainty. In this setting, the variety of possible future states is represented as a set of scenarios lacking any information about the likelihood of occurring. Integrating deep uncertainty into multiobjective decision support increases complexity, calling for the elaboration of appropriate methods and tools. This paper proposes a novel interactive multi-scenario multiobjective approach to support decision-making and trade-off analysis in sustainable forest landscape planning under multiple sources of uncertainty. It includes new preference simulation models aimed at reducing the decision-maker's cognitive load and supporting the preference elicitation process. The proposed approach is applied in a case study of long-term forest landscape planning with four sustainability objectives in twelve scenarios and a forestry expert as the decision-maker. The approach is demonstrated to be efficient in exploring trade-offs in different scenarios, helping the expert gain deep insights into the problem, understand the consequences of alternative strategies, and find the most preferred robust strategy.
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Julkaisija
Canadian Science PublishingISSN Hae Julkaisufoorumista
0045-5067Asiasanat
forest management climate change multiobjective optimization scenario planning partially known preferences tulevaisuus todennäköisyys strateginen suunnittelu ilmastonmuutokset metsänhoito päätöksenteko ympäristön tila monitavoiteoptimointi metsät metsäala kestävä kehitys skenaariot todennäköisyyslaskenta ympäristö
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/151604356
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Suomen AkatemiaRahoitusohjelmat(t)
Profilointi, SA; Akatemiahanke, SALisätietoja rahoituksesta
This research was partly funded by the Academy of Finland (grants no. 322221 and 311877). This research is related to the thematic research area Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO, jyu.fi/demo) of the University of JyaskylaLisenssi
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