A Multi-criteria Resource Selection Method for Software Projects Using Fuzzy Logic
When planning a software project, we must assign resources to tasks. Resource selection is a fundamental step to resource allocation since we first need to find the most suitable candidates for each task before deciding who will actually perform them. In order to rank available resources, we have to evaluate their skills and define the corresponding selection criteria for the tasks. While being the choice of many approaches, representing skill levels by means of ordinal scales and defining selection criteria using binary operations imply some limitations. Pure mathematical approaches are difficult to model and suffer from a partial loss in meaning in terms of knowledge representation. Fuzzy Logic, as an extension to classical sets and logic, uses linguistic variables and a continuous range of truth values for decision and set membership. It allows handling inherent uncertainties in this process, while hiding the complexity from the final user. In this paper we show how Fuzzy Logic can be applied to the resource selection problem. A prototype was built to demonstrate and evaluate the results.
KeywordsResource Selection Software Project Management Fuzzy Logic Knowledge Representation
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- 1.Schwalbe, K.: Information Technology Project Management, Thomson Learning, 2nd edn., Canada (2002)Google Scholar
- 2.Kerzner, H.: Applied project management: best practices on implementation. John Wiley & Sons, Chichester (2000)Google Scholar
- 3.Plekhanova, V.: On Project Management Scheduling where Human Resource is a Critical Variable. In: Gruhn, V. (ed.) EWSPT 1998. LNCS, vol. 1487, pp. 116–121. Springer, Heidelberg (1998)Google Scholar
- 4.Joslin, D., Poole, W.: Agent-Based Simulation for Software Project Planning. In: Proceedings of the 37th Conference on Winter Simulation, pp. 1059–1066 (2005)Google Scholar
- 7.Royce, W.: Software Project Management: A Unified Framework. Addison-Wesley, Reading (1998)Google Scholar
- 8.Otero, L.D., Centeno, G., Torres, A.R., Otero, C.E.: A Systematic Approach of Resource Allocation in Software Projects. Computers & Industrial Engineering 55, 4 (2008)Google Scholar
- 10.Cox, E.D.: Fuzzy Logic for Business and Industry. Charles River Media (1995)Google Scholar
- 12.Plekhanova, V.: Applications of the Profile Theory to Software Engineering and Knowledge Engineering. In: Proceedings of the Twelfth International Conference on Software Engineering and Knowledge Engineering, Knowledge Systems Institute, pp. 133–141 (2000)Google Scholar
- 13.Shen, M., Tzeng, G., Liu, D.: Multi-Criteria Task Assignment in Workflow Management Systems. In: Proceedings of the 36th Hawaii International Conference on System Sciences. IEEE Press, Los Alamitos (2003)Google Scholar
- 14.Acuña, S.T., Juristo, N.: Modelling human competencies in the software process. In: ProSim 2003 (2003)Google Scholar
- 15.Kosko, B.: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall, Englewood Cliffs (1991)Google Scholar
- 16.Callegari, D.A., Bastos, R.M.: A Systematic Review of Dynamic Reconfiguration of Software Projects. In: SBES 2008 - XXII Simpósio Brasileiro de Engenharia de Software, pp. 299–313 (2008)Google Scholar