Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4245
DC FieldValueLanguage
dc.contributor.authorStylianou, Constantinos-
dc.contributor.authorAndreou, Andreas S.-
dc.contributor.otherΑνδρέου, Ανδρέας Σ.-
dc.date2012en
dc.date.accessioned2014-07-10T07:20:39Z-
dc.date.accessioned2015-12-09T12:01:53Z-
dc.date.available2014-07-10T07:20:39Z-
dc.date.available2015-12-09T12:01:53Z-
dc.date.issued2012-09-
dc.identifier.citation8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, Halkidiki, Greece, 27-30 September 2012en_US
dc.identifier.issn1868-4238-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4245-
dc.description.abstractThis paper proposes a multi-objective genetic algorithm for software project team staffing that focuses on optimizing human resource usage based on technical skills and personality traits of software developers. Human factors are recognized as critical aspects affecting the rate of success of software projects, as well as other properties, such as productivity, software quality, performance, and job satisfaction. However, managers often rely solely on technical criteria to staff their projects, which risks overlooking these important aspects of software development, such as the abilities and work styles of developers. The behaviour and scalability of the algorithm was validated against a series of hypothetical projects of varying size and complexity, and also through a real-world project of an SME in the local IT industry. The approach demonstrated a sufficient ability to generate both feasible and optimal staffing solutions by assigning developers most technically competent and suited personality-wise for each project task.en_US
dc.languageenen
dc.language.isoenen_US
dc.rights© 2012 IFIPen_US
dc.subjectFive-Factor Modelen_US
dc.subjectIT industryen_US
dc.subjectMulti-objective genetic algorithmen_US
dc.subjectOptimal staffingen_US
dc.subjectPersonality traitsen_US
dc.subjectPersonality typesen_US
dc.subjectReal world projectsen_US
dc.subjectSoftware developeren_US
dc.subjectSoftware development teamsen_US
dc.subjectSoftware projecten_US
dc.subjectSoftware project managementen_US
dc.subjectSoftware qualityen_US
dc.subjectTeam staffingen_US
dc.subjectTechnical skillsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectComputer software selection and evaluationen_US
dc.subjectGenetic algorithmsen_US
dc.subjectJob satisfactionen_US
dc.subjectProject managementen_US
dc.subjectSoftware designen_US
dc.subjectPersonnel selectionen_US
dc.titleA multi-objective genetic algorithm for software development team staffing based on personality typesen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.reviewPeer Reviewed-
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceIFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovationsen_US
dc.identifier.doi10.1007/978-3-642-33409-2_5en_US
dc.dept.handle123456789/134en
cut.common.academicyear2012-2013en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0001-7104-2097-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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