BAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimization

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorGjoreski, Martinen_US
dc.contributor.authorKuzmanovski, Vladimiren_US
dc.contributor.authorBohanec, Markoen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorLecturer Hollmen Jaakko groupen
dc.contributor.organizationUniversità della Svizzera italianaen_US
dc.contributor.organizationJožef Stefan Instituteen_US
dc.date.accessioned2022-08-10T08:26:19Z
dc.date.available2022-08-10T08:26:19Z
dc.date.issued2022-06en_US
dc.descriptionFunding Information: Funding: This work was partially funded by the Slovenian Research Agency (ARRS) under research core funding Knowledge Technologies No. P2-0103 (B), and by the Slovenian Ministry of Education, Science and Sport (funding agreement No. C3330-17-529020). Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
dc.description.abstractMulti-attribute decision analysis is an approach to decision support in which decision alternatives are evaluated by multi-criteria models. An advanced feature of decision support models is the possibility to search for new alternatives that satisfy certain conditions. This task is important for practical decision support; however, the related work on generating alternatives for qualitative multi-attribute decision models is quite scarce. In this paper, we introduce Bayesian Alternative Generator for Decision Support Models (BAG-DSM), a method to address the problem of generating alternatives. More specifically, given a multi-attribute hierarchical model and an alternative representing the initial state, the goal is to generate alternatives that demand the least change in the provided alternative to obtain a desirable outcome. The brute force approach has exponential time complexity and has prohibitively long execution times, even for moderately sized models. BAGDSM avoids these problems by using a Bayesian optimization approach adapted to qualitative DEX models. BAG-DSM was extensively evaluated and compared to a baseline method on 43 different DEX decision models with varying complexity, e.g., different depth and attribute importance. The comparison was performed with respect to: the time to obtain the first appropriate alternative, the number of generated alternatives, and the number of attribute changes required to reach the generated alternatives. BAG-DSM outperforms the baseline in all of the experiments by a large margin. Additionally, the evaluation confirms BAG-DSM’s suitability for the task, i.e., on average, it generates at least one appropriate alternative within two seconds. The relation between the depth of the multi-attribute hierarchical models—a parameter that increases the search space exponentially— and the time to obtaining the first appropriate alternative was linear and not exponential, by which BAG-DSM’s scalability is empirically confirmed.en
dc.description.versionPeer revieweden
dc.format.extent22
dc.format.extent1-22
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationGjoreski, M, Kuzmanovski, V & Bohanec, M 2022, ' BAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimization ', Algorithms, vol. 15, no. 6, 197, pp. 1-22 . https://doi.org/10.3390/a15060197en
dc.identifier.doi10.3390/a15060197en_US
dc.identifier.issn1999-4893
dc.identifier.otherPURE UUID: cc549bf4-06b8-4a59-9071-241ed752f5caen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/cc549bf4-06b8-4a59-9071-241ed752f5caen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85132304397&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/86155807/BAG_DSM.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/115924
dc.identifier.urnURN:NBN:fi:aalto-202208104746
dc.language.isoenen
dc.publisherMDPI AG
dc.relation.ispartofseriesALGORITHMSen
dc.relation.ispartofseriesVolume 15, issue 6en
dc.rightsopenAccessen
dc.subject.keywordalternativesen_US
dc.subject.keywordBayesian optimizationen_US
dc.subject.keyworddecision supporten_US
dc.subject.keywordmethod DEXen_US
dc.subject.keywordmulti-attribute modelsen_US
dc.titleBAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimizationen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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