SUSTAINABILITY PROJECT: RISK ANALYSIS BASED ON DECISION TREES UNDER CONDITIONS OF TOTAL AND PARTIAL IGNORANCE

dc.contributor.authorDoubravský, Karelcs
dc.contributor.authorDoskočil, Radekcs
dc.contributor.authorDohnal, Mirkocs
dc.coverage.issue3cs
dc.coverage.volume5cs
dc.date.accessioned2022-05-18T10:51:47Z
dc.date.available2022-05-18T10:51:47Z
dc.date.issued2016-04-05cs
dc.description.abstractSustainability project is an important part of project management and depends on many factors, such as financial resources, human resources, scheduling operations and especially potential risks. This paper presents a way to work with uncertain information processing project risk analysis with regard to its sustainability. Risk management is an important part of various disciplines, e.g. Project management, Crisis management, Change management, Information Security Management System, etc. Risk analysis is mostly based on expert estimates. However, this may be a problem with brand new tasks as identification of different threats and their numerical evaluations can be interpreted as a decision-making task which can be formalised as a decision tree. A decision-making task solution requires knowledge of all relevant input information items (III), such as probabilities, penalties and profits. If all those numerical values are known then the well-known methods of decision trees evaluations can be used. However, if complex project management problems are solved then a substantial set of relevant data items is missing or its accuracies are prohibitively low. The aim of this paper is to present easy approach how missing elements of the III set can be obtained and integrated into incomplete data sets. The paper contributes a common sense heuristics to obtain missing elements of the III set which can generate all numerical values, i.e. a problem under complete ignorance is solve, and a reconciliation mechanism based on linear programming which allows results of common sense heuristics simply integrate into incomplete data set, i.e. a problem under partial ignorance is solved. The results are therefore divided into two parts. In the first part solves a problem under total ignorance. The second part of the case study evaluates some unknown probabilities, therefore solves a problem under partial ignorance. Both tasks, i.e. partial and total ignorance are demonstrated using a quasi-realistic decision tree. The decision tree has one root node, 6 lotteries and 15 terminals; the total number of unknown probabilities is 21 under total ignorance and 18 probabilities are evaluated under partial ignorance.en
dc.formattextcs
dc.format.extent391-402cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationJournal of Security and Sustainability Issues. 2016, vol. 5, issue 3, p. 391-402.en
dc.identifier.doi10.9770/jssi.2016.5.3(7)cs
dc.identifier.issn2029-7025cs
dc.identifier.other123512cs
dc.identifier.urihttp://hdl.handle.net/11012/204283
dc.language.isoencs
dc.publisherThe General Jonas Žemaitis Military Academy of Lithuaniacs
dc.relation.ispartofJournal of Security and Sustainability Issuescs
dc.relation.urihttps://journals.lka.lt/journal/jssi/article/1503/infocs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2029-7025/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectProject risksen
dc.subjectsustainability projectsen
dc.subjectdecision treeen
dc.subjecttotal ignoranceen
dc.subjectpartial ignoranceen
dc.subjectreconciliation.en
dc.titleSUSTAINABILITY PROJECT: RISK ANALYSIS BASED ON DECISION TREES UNDER CONDITIONS OF TOTAL AND PARTIAL IGNORANCEen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-123512en
sync.item.dbtypeVAVen
sync.item.insts2022.05.18 12:51:47en
sync.item.modts2022.05.18 12:14:16en
thesis.grantorVysoké učení technické v Brně. Fakulta podnikatelská. Ústav informatikycs
thesis.grantorVysoké učení technické v Brně. Fakulta podnikatelská. Ústav ekonomikycs
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