A robust search-based approach to project management in the presence of abandonment, rework, error and uncertainty

被引:40
作者
Antoniol, G [1 ]
Di Penta, M [1 ]
Harman, M [1 ]
机构
[1] Univ Sannio, Dept Engn, Res Ctr Software Technol, RCOST, I-82100 Benevento, Italy
来源
10TH INTERNATIONAL SYMPOSIUM ON SOFTWARE METRICS, PROCEEDINGS | 2004年
关键词
software project management; genetic algorithms; queuing simulation;
D O I
10.1109/METRIC.2004.1357901
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Managing a large software project involves initial estimates that may turn out to be erroneous or that might be expressed with some degree of uncertainty. Furthermore, as the project progresses, it often becomes necessary to rework some of the work packages that make up the overall project. Other work packages might have to be abandoned for a variety of reasons. In the presence of these difficulties, optimal allocation of staff to project teams and teams to work packages is far from trivial. This paper shows how genetic algorithms can be combined with a queuing simulation model to address these problems in a robust manner A tandem genetic algorithm is used to search for the best sequence in which to process work packages and the best allocation of staff to project teams. The simulation model, that computes the project estimated completion date, guides the search. The possible impact of rework, abandonment and erroneous or uncertain initial estimates are characterised by separate error distributions. The paper presents results from the application of these techniques to data obtained from a large scale commercial software maintenance project.
引用
收藏
页码:172 / 183
页数:12
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