Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4246
DC FieldValueLanguage
dc.contributor.authorStylianou, Constantinos-
dc.contributor.authorAndreou, Andreas S.-
dc.contributor.otherΑνδρέου, Ανδρέας Σ.-
dc.date2011en
dc.date.accessioned2014-07-10T07:20:42Z-
dc.date.accessioned2015-12-09T12:01:53Z-
dc.date.available2014-07-10T07:20:42Z-
dc.date.available2015-12-09T12:01:53Z-
dc.date.issued2011-09-
dc.identifier.citationArtificial Intelligence Applications and Innovations. EANN 2011, AIAI 2011. IFIP Advances in Information and Communication Technology, vol 364en_US
dc.identifier.isbn978-3-642-23960-1-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4246-
dc.description.abstractSoftware development organisations are under heavy pressure to complete projects on time, within budget and with the appropriate level of quality, and many questions are asked when a project fails to meet any or all of these requirements. Over the years, much research effort has been spent to find ways to mitigate these failures, the reasons of which come from both within and outside the organisation's control. One possible risk of failure lies in human resource management and, since humans are the main asset of software organisations, getting the right team to do the job is critical. This paper proposes a procedure for software project managers to support their project scheduling and team staffing activities - two areas where human resources directly impact software development projects and management decisions - by adopting a genetic algorithm approach as an optimisation technique to help solve software project scheduling and team staffing problems.en_US
dc.formatpdfen_US
dc.languageenen
dc.language.isoenen_US
dc.rights© IFIP International Federation for Information Processingen_US
dc.subjectGenetic algorithm approachen_US
dc.subjectIntelligent softwareen_US
dc.subjectManagement decisionsen_US
dc.subjectOptimisationsen_US
dc.subjectProject schedulingen_US
dc.subjectResearch effortsen_US
dc.subjectRisk of failureen_US
dc.subjectSoftware development projectsen_US
dc.subjectSoftware projecten_US
dc.subjectSoftware project managementen_US
dc.subjectTeam staffingen_US
dc.subjectArtificial intelligenceen_US
dc.subjectEnterprise resource managementen_US
dc.subjectGenetic algorithmsen_US
dc.subjectPersonnelen_US
dc.subjectPersonnel selectionen_US
dc.subjectPersonnel selectionen_US
dc.subjectProject managementen_US
dc.subjectScheduling algorithmsen_US
dc.subjectSoftware designen_US
dc.titleIntelligent software project scheduling and team staffing with genetic algorithmsen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of Cyprusen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Artificial Intelligence Applications and Innovationsen_US
dc.identifier.doi10.1007/978-3-642-23960-1_21en_US
dc.dept.handle123456789/134en
cut.common.academicyear2011-2012en_US
item.openairetypeconferenceObject-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
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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