Abstract
Most of the studies on project scheduling problems assume that every assigned participant or every team of the same number of participants, completes tasks with an equal efficiency, but this is usually not the case for real world problems. This paper presents a more realistic and complex model with extra consideration on team efficiency which are quantitatively measured on employee-task assignment. This study demonstrates the impacts of team efficiency in a well-studied software project management problem. Moreover, this study illustrates how a heuristic optimization method, population-based incremental learning, copes with such added complexity. The experimental results show that the resulting near optimal solutions not only satisfy constraints, but also reflect the impacts of team efficiency. The findings will hopefully motivate future studies on comprehensive understandings of the quality and efficiency of team work.
| Original language | English |
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| Title of host publication | Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 3016-3023 |
| Number of pages | 8 |
| ISBN (Print) | 9781479914883 |
| DOIs | |
| Publication status | Published - 16 Sept 2014 |
| Event | 2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014 |
Conference
| Conference | 2014 IEEE Congress on Evolutionary Computation, CEC 2014 |
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| Country/Territory | China |
| City | Beijing |
| Period | 6/07/14 → 11/07/14 |
ASJC Scopus subject areas
- Artificial Intelligence
- Computational Theory and Mathematics
- Theoretical Computer Science