Abstract
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.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Schwalbe, K.: Information Technology Project Management, Thomson Learning, 2nd edn., Canada (2002)
Kerzner, H.: Applied project management: best practices on implementation. John Wiley & Sons, Chichester (2000)
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)
Joslin, D., Poole, W.: Agent-Based Simulation for Software Project Planning. In: Proceedings of the 37th Conference on Winter Simulation, pp. 1059–1066 (2005)
Cugola, G., Di Nitto, E., Fuggetta, A., Ghezzi, C.: A framework for formalizing inconsistencies and deviations in human-centered systems. ACM Transactions on Software Engineering 5(3), 191–230 (1996)
Acuña, S.T., Juristo, N., Moreno, A.M.: Emphasizing Human Capabilities in Software Development. IEEE Software 23(2), 94–101 (2006)
Royce, W.: Software Project Management: A Unified Framework. Addison-Wesley, Reading (1998)
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)
Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)
Cox, E.D.: Fuzzy Logic for Business and Industry. Charles River Media (1995)
Ozdamar, L., Alanya, E.: Uncertainty modelling in software development projects (with case study). Annals of Operations Research 102(6), 157–178 (2001)
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)
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)
Acuña, S.T., Juristo, N.: Modelling human competencies in the software process. In: ProSim 2003 (2003)
Kosko, B.: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall, Englewood Cliffs (1991)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Callegari, D.A., Bastos, R.M. (2009). A Multi-criteria Resource Selection Method for Software Projects Using Fuzzy Logic. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2009. Lecture Notes in Business Information Processing, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01347-8_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-01347-8_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01346-1
Online ISBN: 978-3-642-01347-8
eBook Packages: Computer ScienceComputer Science (R0)