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dc.contributor.authorShavazipour, Babooshka
dc.contributor.authorPodkopaev, Dmitry
dc.contributor.authorMiettinen, Kaisa
dc.date.accessioned2022-08-16T06:32:27Z
dc.date.available2022-08-16T06:32:27Z
dc.date.issued2022
dc.identifier.citationShavazipour, B., Podkopaev, D., & Miettinen, K. (2022). Interactive decision support and trade-off analysis for sustainable forest landscape planning under deep uncertainty. <i>Canadian Journal of Forest Research</i>, <i>52</i>(11), 1423-1438. <a href="https://doi.org/10.1139/cjfr-2022-0084" target="_blank">https://doi.org/10.1139/cjfr-2022-0084</a>
dc.identifier.otherCONVID_151604356
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/82565
dc.description.abstractSustainable 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.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherCanadian Science Publishing
dc.relation.ispartofseriesCanadian Journal of Forest Research
dc.rightsIn Copyright
dc.subject.otherforest management
dc.subject.otherclimate change
dc.subject.othermultiobjective optimization
dc.subject.otherscenario planning
dc.subject.otherpartially known preferences
dc.titleInteractive decision support and trade-off analysis for sustainable forest landscape planning under deep uncertainty
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202208164109
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiainePäätöksen teko monitavoitteisestifi
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineMultiobjective Optimization Groupen
dc.contributor.oppiaineDecision analytics utilizing causal models and multiobjective optimizationen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange1423-1438
dc.relation.issn0045-5067
dc.relation.numberinseries11
dc.relation.volume52
dc.type.versionacceptedVersion
dc.rights.copyright© Authors, 2022
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber311877
dc.relation.grantnumber322221
dc.subject.ysotulevaisuus
dc.subject.ysotodennäköisyys
dc.subject.ysostrateginen suunnittelu
dc.subject.ysoilmastonmuutokset
dc.subject.ysometsänhoito
dc.subject.ysopäätöksenteko
dc.subject.ysoympäristön tila
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysometsät
dc.subject.ysometsäala
dc.subject.ysokestävä kehitys
dc.subject.ysoskenaariot
dc.subject.ysotodennäköisyyslaskenta
dc.subject.ysoympäristö
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p817
jyx.subject.urihttp://www.yso.fi/onto/yso/p16014
jyx.subject.urihttp://www.yso.fi/onto/yso/p13653
jyx.subject.urihttp://www.yso.fi/onto/yso/p5729
jyx.subject.urihttp://www.yso.fi/onto/yso/p7534
jyx.subject.urihttp://www.yso.fi/onto/yso/p8743
jyx.subject.urihttp://www.yso.fi/onto/yso/p4342
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p5454
jyx.subject.urihttp://www.yso.fi/onto/yso/p7691
jyx.subject.urihttp://www.yso.fi/onto/yso/p8470
jyx.subject.urihttp://www.yso.fi/onto/yso/p3296
jyx.subject.urihttp://www.yso.fi/onto/yso/p4746
jyx.subject.urihttp://www.yso.fi/onto/yso/p6033
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1139/cjfr-2022-0084
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramResearch profiles, AoFen
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramProfilointi, SAfi
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundinginformationThis 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 Jyaskyla
dc.type.okmA1


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