<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/C03F9CF1-F039-4466-B890-D137ECF230D1"><efrbr-work:titleOfTheWork>Simulating agents as balanced scorecard objectives</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/C03F9CF1-F039-4466-B890-D137ECF230D1"><efrbr-expression:titleOfTheExpression>Simulating agents as balanced scorecard objectives</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Πλήρης Δημοσίευση σε Συνέδριο
            Conference Full Paper
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-11-05</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2008</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>Balanced Scorecard is a measurement system which organizations apply for monitoring their strategic goals. Although this way it is possible to assess the progress of each goal, there is no structured way to reconsider resource allocation to those goals and to plan an optimal allocation scheme. In this paper we use a methodology that matches each goal with an autonomous entity (agent). We let agents deploy their own resources sharing behaviour during simulation time. The overall performance is evaluated through a set of functions and genetic algorithms are used to suggest approximate optimal behaviour’s schemes. Finally, results from the implementation of the methodology on a scorecard of a real organization are presented.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="page range">121-126 </efrbr-expression:note><efrbr-expression:note type="conference name">International Conference on Distributed Human-Machine Systems</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~nmatsatsinis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Matsatsinis Nikolaos
            Ματσατσινης Νικολαος
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="http://users.isc.tuc.gr/~adoulamis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Doulamis Anastasios
            Δουλαμης Αναστασιος
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            Delias Pavlos
            Δελιας Παυλος
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