Abstract
In software development, testing and maintenance, as in other large scale engineering activities, effective project planning is essential. Failure to plan and/or poor planning can cause delays and costs that, given timing and budget constraints, are often unacceptable, leading to business–critical failures. Traditional tools such as the Project Evaluation and Review Technique (PERT), the Critical Path Method (CPM), Gantt diagrams and Earned Value Analysis help to plan and track project milestones. While these tools and techniques are important, they cannot assist with the identification of optimal scheduling assignment in the presence of configurable resource allocation. However, most large scale software projects involve several teams of programmers and many individual project work packages. As such, the optimal allocation of teams of programmers (the primary resource cost drivers) to Work Packages (WPs) is an important problem which cannot be overlooked.
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References
Antoniol, G., Cimitile, A., Di Lucca, G.A., Di Penta, M.: Assessing staffing needs for a software maintenance project through queuing simulation. IEEE Transactions on Software Engineering 30(1), 43–58 (2004)
Davis, L.: Job-shop scheduling with genetic algorithms. In: International Conference on GAs, pp. 136–140. Lawrence Erlbaum, Mahwah (1985)
Falkenauer, E.: Genetic Algorithms and Grouping Problems. Wiley-Inter Science, Wiley-NY (1998)
Hart, E., Corne, D., Ross, P.: The state of the art in evolutionary scheduling. In: Genetic Programming and Evolvable Machines (2004) (to appear)
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© 2004 Springer-Verlag Berlin Heidelberg
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Antoniol, G., Di Penta, M., Harman, M. (2004). Search-Based Techniques for Optimizing Software Project Resource Allocation. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_162
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DOI: https://doi.org/10.1007/978-3-540-24855-2_162
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