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The Scientific World Journal
Volume 2014, Article ID 731081, 7 pages
http://dx.doi.org/10.1155/2014/731081
Research Article

Scheduling Projects with Multiskill Learning Effect

College of Management and Economics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China

Received 3 November 2013; Accepted 24 December 2013; Published 10 February 2014

Academic Editors: Q. Cheng and J. Yang

Copyright © 2014 Hong Zha and Lianying Zhang. 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. S. Hartmann and D. Briskorn, “A survey of variants and extensions of the resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 207, no. 1, pp. 1–14, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. E. Alba and J. Francisco Chicano, “Software project management with GAs,” Information Sciences, vol. 177, no. 11, pp. 2380–2401, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. H. Li and K. Womer, “Scheduling projects with multi-skilled personnel by a hybrid MILP/CP benders decomposition algorithm,” Journal of Scheduling, vol. 12, no. 3, pp. 281–298, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. C. Heimerl and R. Kolisch, “Scheduling and staffing multiple projects with a multi-skilled workforce,” OR Spectrum, vol. 32, no. 2, pp. 343–368, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. V. Yannibelli and A. Amandi, “A knowledge-based evolutionary assistant to software development project scheduling,” Expert Systems with Applications, vol. 38, no. 7, pp. 8403–8413, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. M. J. Anzanello and F. S. Fogliatto, “Learning curve models and applications: literature review and research directions,” International Journal of Industrial Ergonomics, vol. 41, no. 5, pp. 573–583, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. D. Biskup, “A state-of-the-art review on scheduling with learning effects,” European Journal of Operational Research, vol. 188, no. 2, pp. 315–329, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. M. J. Anzanello and F. S. Fogliatto, “Learning curve models and applications: literature review and research directions,” International Journal of Industrial Ergonomics, vol. 41, no. 5, pp. 573–583, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. T. E. Cheng and G. Wang, “Single machine scheduling with learning effect considerations,” Annals of Operations Research, vol. 98, no. 1–4, pp. 273–290, 2000. View at Google Scholar · View at Scopus
  10. D. Biskup and D. Simons, “Common due date scheduling with autonomous and induced learning,” European Journal of Operational Research, vol. 159, no. 3, pp. 606–616, 2004. View at Publisher · View at Google Scholar · View at Scopus
  11. J.-B. Wang, “A note on scheduling problems with learning effect and deteriorating jobs,” International Journal of Systems Science, vol. 37, no. 12, pp. 827–833, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. W.-H. Kuo and D.-L. Yang, “Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect,” European Journal of Operational Research, vol. 174, no. 2, pp. 1184–1190, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. R. Rudek, “The single processor total weighted completion time scheduling problem with the sum-of-processing-time based learning model,” Information Sciences, vol. 199, pp. 216–229, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. C.-C. Wu and W.-C. Lee, “Single-machine and flowshop scheduling with a general learning effect model,” Computers and Industrial Engineering, vol. 56, no. 4, pp. 1553–1558, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. Y.-Y. Lu, C.-M. Wei, and J.-B. Wang, “Several single-machine scheduling problems with general learning effects,” Applied Mathematical Modelling, vol. 36, no. 11, pp. 5650–5656, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. M.-C. Wu and S.-H. Sun, “A project scheduling and staff assignment model considering learning effect,” International Journal of Advanced Manufacturing Technology, vol. 28, no. 11-12, pp. 1190–1195, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. A. Janiak and R. Rudek, “A note on a makespan minimization problem with a multi-ability learning effect,” Omega, vol. 38, no. 3-4, pp. 213–217, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. C. Heimerl and R. Kolisch, “Work assignment to and qualification of multi-skilled human resources under knowledge depreciation and company skill level targets,” International Journal of Production Research, vol. 48, no. 13, pp. 3759–3781, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. W.-H. Kuo and D.-L. Yang, “Minimizing the makespan in a single machine scheduling problem with a time-based learning effect,” Information Processing Letters, vol. 97, no. 2, pp. 64–67, 2006. View at Publisher · View at Google Scholar · View at Scopus
  20. D. E. Goldberg and J. H. Holland, “Genetic algorithms and machine learning,” Machine Learning, vol. 3, no. 2, pp. 95–99, 1988. View at Google Scholar
  21. R. Kolisch and S. Hartmann, “Experimental investigation of heuristics for resource-constrained project scheduling: an update,” European Journal of Operational Research, vol. 174, no. 1, pp. 23–37, 2006. View at Publisher · View at Google Scholar · View at Scopus
  22. K. Moumene and J. A. Ferland, “Activity list representation for a generalization of the resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 199, no. 1, pp. 46–54, 2009. View at Publisher · View at Google Scholar · View at Scopus
  23. R. Kolisch, “Serial and parallel resource-constrained project scheduling methods revisited: theory and computation,” European Journal of Operational Research, vol. 90, no. 2, pp. 320–333, 1996. View at Google Scholar · View at Scopus
  24. L. Ford and D. Fulkerson, “Maximal flow through a network,” Canadian Journal of Mathematics, vol. 8, pp. 399–404, 1956. View at Publisher · View at Google Scholar
  25. J. Yang and Z. Fei, “Bipartite graph based dynamic spectrum allocation for wireless mesh networks,” in Proceedings of the 28th International Conference on Distributed Computing Systems Workshops (ICDCS '08), pp. 96–101, IEEE press, June 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. C. Liu, G. Chang, and J. Jia, “A new channel assignment algorithm in wireless mesh network,” in Recent Advances in Computer Science and Information EngIneerIng, vol. 127 of Lecture Notes in Electrical Engineering, pp. 511–516, 2012. View at Google Scholar