Abstract | ||
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Task assignments and scheduling have always been crucial to the software development process, and the quality of those assignments will greatly influence the success of a project. During the software project management process, it is intuitive but often neglected to assign the right people to do the right task. Our earlier models, task-based model and timeline-based model, applied genetic algorithms (GAs) to software project scheduling problems. This paper extends those works by proposing a capability-based scheduling framework, in which personnel/team capability, is simulated. The new model is described along with a new GA that produces optimal or near-optimal schedules. Simulation results show that this new model enhances the ability of GA-based approaches and provides decision support under more realistic conditions. |
Year | DOI | Venue |
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2006 | 10.1109/CIMCA.2006.63 | CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ... |
Keywords | Field | DocType |
genetic algorithms,capability-based scheduling framework,right people,capability-based project scheduling,new model,task-based model,software project management process,earlier model,software project scheduling problem,new ga,timeline-based model,software development process,decision support systems,project management,software project management,software engineering,project scheduling,genetic algorithm,decision support,scheduling | Schedule (project management),Computer science,Two-level scheduling,Software development process,Artificial intelligence,Project management,Distributed computing,Industrial engineering,Fair-share scheduling,Software project management,Schedule,Dynamic priority scheduling,Machine learning | Conference |
Volume | Issue | ISSN |
null | null | null |
ISBN | Citations | PageRank |
0-7695-2731-0 | 3 | 0.41 |
References | Authors | |
1 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Yujia Ge | 1 | 78 | 6.26 |
Carl Chang | 2 | 12 | 1.91 |