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[{"key": "dc.contributor.advisor", "value": "Silvennoinen, Johanna", "language": null, "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Tulenvuo, Sylvia", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2024-05-27T08:48:08Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2024-05-27T08:48:08Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2024", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/95214", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Solving problems that involve considering multiple conflicting objective functions simultaneously is called multiobjective optimisation. Multiple mathematically equally good solutions can be found to these problems. These solutions are called Pareto optimal solutions. In order to choose one of these solutions as the final solution of the multiobjective optimisation problem considered, more information is required. This information is acquired from a decision-maker. The decision-maker is assumed to be an expert regarding the optimisation problem to be solved, and preference information provided by them is exploited to generate solutions that fit the decision maker\u2019s preferences. Multiobjective optimisation methods can be classified based on how the preference information is given. Methods where preference information is given progressively during the decision process are called interactive methods. Interactive methods repeat steps of the solution process until the decision-maker is satisfied and confident about the final solution. Interactive methods place a significant role on the decision-maker in solving the multiobjective optimisation problem. Despite the importance of the decision-maker, the literature lacks a validated measurement instrument to help develop and improve interactive methods to better match the needs and constraints of the decision-maker. The goal of this thesis was to examine whether research data from a previous study can be utilised to form a reliable scale or scales to assess interactive multiobjective optimisation methods. Principal component analysis was conducted to identify the components from the research data (N = 164). Three components were found: Cognitive load, Satisfaction and Decision-making support. Each component was calculated into a sum variable and their internal consistency was evaluated using Cronbach\u2019s alpha. Cronbach\u2019s alpha values were at an acceptable level. The correlations between the components indicate that they measure distinct constructs of interaction between the decision-maker and the interactive multiobjective optimisation methods and are therefore best utilised as individual scales. More research is needed in order to evaluate the validity of these scales.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Monitavoiteoptimointi on ongelmanratkaisua, jossa tulee yht\u00e4aikaisesti ottaa huomioon useampi kesken\u00e4\u00e4n ristiriidassa oleva tavoitefunktio. Monitavoi-teoptimoinnin ongelmiin on l\u00f6ydett\u00e4viss\u00e4 useita matemaattisesti kesken\u00e4\u00e4n yht\u00e4 hyvi\u00e4 ratkaisuja. N\u00e4it\u00e4 ratkaisuja kutsutaan Pareto-optimaalisiksi ratkaisuiksi. Lis\u00e4tietoa tarvitaan, jotta jokin n\u00e4ist\u00e4 ratkaisuista voitaisiin valita ratkaistavan monitavoiteoptimointiongelman lopulliseksi ratkaisuksi. T\u00e4m\u00e4 lis\u00e4tieto saadaan p\u00e4\u00e4t\u00f6ksentekij\u00e4lt\u00e4. P\u00e4\u00e4t\u00f6ksentekij\u00e4n, jonka oletetaan olevan ratkaistavan monitavoiteoptimointiongelman asiantuntija, tarjoamaa preferenssitietoa hy\u00f6dynnet\u00e4\u00e4n h\u00e4nen preferensseihins\u00e4 sopivien vastausten luomiseksi. Monitavoiteoptimointimenetelmi\u00e4 on useita erilaisia, ja ne voidaan luokitella sen mukaan, miten preferenssitietoa annetaan. Vuorovaikutteisissa monitavoiteoptimointimenetelmiss\u00e4 p\u00e4\u00e4t\u00f6ksentekij\u00e4 antaa preferenssitietoa pikkuhiljaa, ohjaten samalla p\u00e4\u00e4t\u00f6ksentekoprosessia, kunnes h\u00e4n on tyytyv\u00e4inen lopulliseen ratkaisuun. P\u00e4\u00e4t\u00f6ksentekij\u00e4ll\u00e4 on t\u00e4rke\u00e4 rooli sopivan ratkaisun l\u00f6yt\u00e4misess\u00e4, mutta alalta puuttuu validoitu mittari, jonka avulla voitaisiin paremmin tutkia p\u00e4\u00e4t\u00f6ksentekij\u00e4\u00e4 sek\u00e4 p\u00e4\u00e4t\u00f6ksentekoa vuorovaikutteisia monitavoiteoptimoinnin menetelmi\u00e4 k\u00e4ytett\u00e4ess\u00e4. T\u00e4ss\u00e4 tutkimuksessa oli tavoitteena selvitt\u00e4\u00e4, voiko aiemmasta tutkimusmateriaalista koostaa luotettavan mittarin tai mittareita, joilla voitaisiin arvioida vuorovaikutteisia monitavoiteoptimoinnin menetelmi\u00e4. Tutkimusdatan (N = 164) analysoinnissa hy\u00f6dynnettiin p\u00e4\u00e4komponenttianalyysi\u00e4, jonka avulla tunnistettiin datasta l\u00f6ytyv\u00e4t kolme komponenttia. N\u00e4m\u00e4 kolme komponenttia nimettiin seuraavasti: Kognitiivinen kuormitus, Tyytyv\u00e4isyys, ja P\u00e4\u00e4t\u00f6ksenteon tukeminen. Komponenteista laskettiin keskiarvosummamuuttujat, joiden sis\u00e4inen konsistenssi tarkastettiin Cronbachin alfan avulla. Komponenttien v\u00e4liset korrelaatiot osoittavat, ett\u00e4 ne mittaavat p\u00e4\u00e4t\u00f6ksentekij\u00e4n ja interaktiivisen monitavoiteoptimointimenetelm\u00e4n v\u00e4lisen vuorovaikutuksen erillisi\u00e4 osa-alueita, ja ovat t\u00e4ten parhaiten hy\u00f6dynnett\u00e4viss\u00e4 yksitt\u00e4isin\u00e4 mittareina. Mittareiden validiteetin arviointi vaatii jatkotutkimusta.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2024-05-27T08:48:08Z\r\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2024-05-27T08:48:08Z (GMT). No. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "60", "language": null, "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "CC BY 4.0", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "Developing a set of scales to assess interactive multiobjective optimisation methods", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202405273978", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Kognitiotiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Cognitive Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.copyright", "value": "\u00a9 The Author(s)", "language": null, "element": "rights", "qualifier": "copyright", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://creativecommons.org/licenses/by/4.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
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