Table of Contents
Advances in Software Engineering
Volume 2015, Article ID 695873, 15 pages
http://dx.doi.org/10.1155/2015/695873
Research Article

On Using Fuzzy Linguistic 2-Tuples for the Evaluation of Human Resource Suitability in Software Development Tasks

1Department of Business Administration, Project Management Direction of Studies, Technological Educational Institute of Thessaly, 41110 Larissa, Greece
2Centre for Research and Technology, Institute of Research and Technology of Thessaly, 38333 Volos, Greece
3Department of Wood and Furniture Design and Technology, Technological Educational Institute of Thessaly, 43100 Karditsa, Greece

Received 24 March 2015; Accepted 9 June 2015

Academic Editor: Phillip A. Laplante

Copyright © 2015 Vassilis C. Gerogiannis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. A. Callegari and R. M. Bastos, “A multi-criteria resource selection method for software projects using fuzzy logic,” in Enterprise Information Systems, J. Filipe and J. Cordeiro, Eds., vol. 24 of Lecture Notes in Business Information Processing, pp. 376–388, Springer, Berlin, Germany, 2009. View at Publisher · View at Google Scholar
  2. L. D. Otero, G. Centeno, A. J. Ruiz-Torres, and C. E. Otero, “A systematic approach for resource allocation in software projects,” Computers and Industrial Engineering, vol. 56, no. 4, pp. 1333–1339, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. S. T. Acuña, N. Juristo, and A. M. Moreno, “Emphasizing human capabilities in software development,” IEEE Software, vol. 23, no. 2, pp. 94–101, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. F. Padberg, “Scheduling software projects to minimize the development time and cost with a given staff,” in Proceedings of the Software Engineering Conference (APSEC '01), pp. 187–194, 2001.
  5. L. D. Otero and C. E. Otero, “A fuzzy expert system architecture for capability assessments in skill-based environments,” Expert Systems with Applications, vol. 39, no. 1, pp. 654–662, 2012. View at Publisher · View at Google Scholar · View at Scopus
  6. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965. View at Google Scholar · View at MathSciNet
  7. F. Herrera and L. Martínez, “A 2-tuple fuzzy linguistic representation model for computing with words,” IEEE Transactions on Fuzzy Systems, vol. 8, no. 6, pp. 746–752, 2000. View at Google Scholar
  8. X. Liao, Y. Li, and B. Lu, “A model for selecting an ERP system based on linguistic information processing,” Information Systems, vol. 32, no. 7, pp. 1005–1017, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. V. C. Gerogiannis, E. Rapti, A. Karageorgos, and P. Fitsilis, “Human resource assessment in software development projects using fuzzy linguistic 2-tuples,” in Proceedings of the 2nd International Conference on Artificial Intelligence, Modelling & Simulation (AIMS '14), pp. 217–222, IEEE, Madrid, Spain, November 2014. View at Publisher · View at Google Scholar
  10. V. C. Gerogiannis, E. Rapti, A. Karageorgos, and P. Fitsilis, “A fuzzy linguistic approach for human resource evaluation and selection in software projects,” in Proceedings of the 5th International Conference on Industrial Engineering and Operations Management (IEOM' 15), pp. 1–9, Dubai, UAE, March 2015. View at Publisher · View at Google Scholar
  11. SPRINT SMEs Project, January 2015, http://sprint.teilar.gr/.
  12. V. C. Gerogiannis, G. Kakarontzas, L. Anthopoulos, S. Bibi, and I. Stamelos, “The SPRINT-SMEs approach for software process improvement in small-medium sized software development enterprises,” in Proceedings of the Scientific Workshop of R&D Projects in ARCHIMEDES III Research Programme, Technological Education Institute of Thessaly, Larissa, Greece, November 2013.
  13. S. Bibi, V. C. Gerogiannis, G. Kakarontzas, and I. Stamelos, “Ontology based bayesian software process improvenent,” in Proceedings of the 9th International Conference on Software Engineering and Applications (ICSOFT-EA '14), pp. 568–575, Vienna, Austria, August 2014. View at Publisher · View at Google Scholar
  14. M. André, M. G. Baldoquín, and S. T. Acuña, “Formal model for assigning human resources to teams in software projects,” Information and Software Technology, vol. 53, no. 3, pp. 259–275, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. H. I. Ahmad, A systematic review of selection and management of a project team [M.S. thesis], Joensuu School of Computing, Faculty of Science and Forestry, University of Eastern Finland, 2013.
  16. T. J. A. Santos, A. M. Lima, C. A. Reis, and R. Q. Reis, “Automated support for human resource allocation in software process by cluster analysis,” in Proceedings of the 4th International Workshop Recommendation Systems for Software Engineering, pp. 30–31, Hyderabad, India, June 2014. View at Publisher · View at Google Scholar
  17. A. Barreto, M. D. O. Barros, and C. M. L. Werner, “Staffing a software project: a constraint satisfaction and optimization-based approach,” Computers and Operations Research, vol. 35, no. 10, pp. 3073–3089, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. L. C. e Silva and A. P. C. S. Costa, “Decision model for allocating human resources in information system projects,” International Journal of Project Management, vol. 31, no. 1, pp. 100–108, 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. R. Kolisch, “Resource allocation capabilities of commercial project management software packages,” Interfaces, vol. 29, no. 4, pp. 19–31, 1999. View at Publisher · View at Google Scholar · View at Scopus
  20. O. Zwikael and E. Unger-Aviram, “HRM in project groups: the effect of project duration on team development effectiveness,” International Journal of Project Management, vol. 28, no. 5, pp. 413–421, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. H.-T. Tsai, H. Moskowitz, and L.-H. Lee, “Human resource selection for software development projects using Taguchi's parameter design,” European Journal of Operational Research, vol. 151, no. 1, pp. 167–180, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  22. M. Yoshimura, Y. Fujimi, K. Izui, and S. Nishiwaki, “Decision-making support system for human resource allocation in product development projects,” International Journal of Production Research, vol. 44, no. 5, pp. 831–848, 2006. View at Publisher · View at Google Scholar · View at Scopus
  23. D. Kang, J. Jung, and D.-H. Bae, “Constraint-based human resource allocation in software projects,” Software: Practice and Experience, vol. 41, no. 5, pp. 551–577, 2011. View at Publisher · View at Google Scholar · View at Scopus
  24. W. W. Chu and P. Ngai, “A dynamic constraint-directed ordered search algorithm for solving constraint satisfaction problems,” in Proceedings of the 1st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE '88), pp. 116–125, 1988. View at Publisher · View at Google Scholar
  25. W. Kwak, Y. Shi, and K. Jung, “Human resource allocation in a CPA firm: a fuzzy set approach,” Review of Quantitative Finance and Accounting, vol. 20, no. 3, pp. 277–290, 2003. View at Publisher · View at Google Scholar · View at Scopus
  26. M. L. Hussein and M. A. Abo-Sinna, “A fuzzy dynamic approach to the multicriterion resource allocation problem,” Fuzzy Sets and Systems, vol. 69, no. 2, pp. 115–124, 1995. View at Publisher · View at Google Scholar · View at MathSciNet
  27. D. Strnad and N. Guid, “A fuzzy-genetic decision support system for project team formation,” Applied Soft Computing Journal, vol. 10, no. 4, pp. 1178–1187, 2010. View at Publisher · View at Google Scholar · View at Scopus
  28. N. A. Ruskova, “Decision support system for human resources appraisal and selection,” in Proceedings of the 1st International IEEE Symposium on Intelligent Systems (IS '02), pp. 354–357, IEEE, Varna, Bulgaria, 2002. View at Publisher · View at Google Scholar
  29. J. Dodangeh, S. Sorooshian, and A. R. Afshari, “Linguistic extension for group multicriteria project manager selection,” Journal of Applied Mathematics, vol. 2014, Article ID 570398, 8 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  30. R. M. Rodriguez and L. Martinez, “An analysis of symbolic linguistic computing models in decision making,” International Journal of General Systems, vol. 42, no. 1, pp. 121–136, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  31. L. Martinez and F. Herrera, “An overview on the 2-tuple linguistic model for computing with words in decision making: extensions, applications and challenges,” Information Sciences, vol. 207, pp. 1–18, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  32. T. Da and Y. Xu, “Evaluation on functions of urban waterfront redevelopment based on proportional 2-tuple linguistic,” International Journal of Computational Intelligence Systems, vol. 7, no. 4, pp. 796–808, 2014. View at Publisher · View at Google Scholar
  33. M. Dursun and E. E. Karsak, “A fuzzy MCDM approach for personnel selection,” Expert Systems with Applications, vol. 37, no. 6, pp. 4324–4330, 2010. View at Publisher · View at Google Scholar · View at Scopus
  34. H. Raoudha, D. E. Mouloudi, H. Selma, and E. M. Abderrahman, “A new approach for an efficient human resource appraisal and selection,” Journal of Industrial Engineering and Management, vol. 5, no. 2, pp. 323–343, 2012. View at Publisher · View at Google Scholar · View at Scopus
  35. M. Espinilla, R. de Andrés, F. J. Martinez, and L. Martinez, “A 360-degree performance appraisal model dealing with heterogeneous information and dependent criteria,” Information Sciences, vol. 222, pp. 459–471, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  36. F. Herrera and L. Martinez, “The 2-tuple linguistic computational model. advantages of its linguistic description, accuracy and consistency,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 9, no. 1, pp. 33–48, 2001. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  37. F. Herrera, E. Herrera-Viedma, and J. L. Verdegay, “A rational consensus model in group decision making using linguistic assessments,” Fuzzy Sets and Systems, vol. 88, no. 1, pp. 31–49, 1997. View at Publisher · View at Google Scholar · View at Scopus
  38. F. Herrera, L. Martínez, and P. J. Sánchez, “Managing non-homogeneous information in group decision making,” European Journal of Operational Research, vol. 166, no. 1, pp. 115–132, 2005. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus