DocumentCode
239176
Title
Heuristic optimization for software project management with impacts of team efficiency
Author
Nanlin Jin ; Xin Yao
Author_Institution
Dept. of Comput. Sci. & Digital Technol., Northumbria Univ., Newcastle upon Tyne, UK
fYear
2014
fDate
6-11 July 2014
Firstpage
3016
Lastpage
3023
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.
Keywords
learning (artificial intelligence); optimisation; project management; software management; team working; employee-task assignment; heuristic optimization method; population-based incremental learning; project scheduling problems; software project management problem; team efficiency; Genetic algorithms; Heuristic algorithms; Optimization; Project management; Software; Software algorithms; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6626-4
Type
conf
DOI
10.1109/CEC.2014.6900527
Filename
6900527
Link To Document