Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4246
Title: | Intelligent software project scheduling and team staffing with genetic algorithms | Authors: | Stylianou, Constantinos Andreou, Andreas S. |
metadata.dc.contributor.other: | Ανδρέου, Ανδρέας Σ. | Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Genetic algorithm approach;Intelligent software;Management decisions;Optimisations;Project scheduling;Research efforts;Risk of failure;Software development projects;Software project;Software project management;Team staffing;Artificial intelligence;Enterprise resource management;Genetic algorithms;Personnel;Personnel selection;Personnel selection;Project management;Scheduling algorithms;Software design | Issue Date: | Sep-2011 | Source: | Artificial Intelligence Applications and Innovations. EANN 2011, AIAI 2011. IFIP Advances in Information and Communication Technology, vol 364 | Conference: | International Conference on Artificial Intelligence Applications and Innovations | Abstract: | Software 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. | URI: | https://hdl.handle.net/20.500.14279/4246 | ISBN: | 978-3-642-23960-1 | DOI: | 10.1007/978-3-642-23960-1_21 | Rights: | © IFIP International Federation for Information Processing | Type: | Conference Papers | Affiliation : | Cyprus University of Technology University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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