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The Scientific World Journal
Volume 2013, Article ID 636484, 11 pages
http://dx.doi.org/10.1155/2013/636484
Research Article

Discrete Particle Swarm Optimization with Scout Particles for Library Materials Acquisition

1Institute of Information Management, National Chiao Tung University, Hsinchu 30010, Taiwan
2Department of Computer Science and Information Engineering, Ming Chuan University, Taoyuan 33348, Taiwan

Received 3 June 2013; Accepted 10 July 2013

Academic Editors: S. Balochian, V. Bhatnagar, and Y. Zhang

Copyright © 2013 Yi-Ling Wu 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. J. Harrell, “Literature of acquisitions in review, 2008–9,” Library Resources and Technical Services, vol. 56, no. 1, pp. 4–13, 2012. View at Google Scholar · View at Scopus
  2. W. H. Walters, “Journal prices, book acquisitions, and sustainable college library collections,” College and Research Libraries, vol. 69, no. 6, pp. 576–586, 2008. View at Google Scholar · View at Scopus
  3. L. S. Connaway, K. Downing, Y. Du et al., “2010 top ten trends in academic libraries,” College and Research Libraries News, vol. 71, no. 6, pp. 286–292, 2010. View at Google Scholar · View at Scopus
  4. M. H. Beilby and T. H. Mott Jr., “Academic library acquisitions allocation based on multiple collection development goals,” Computers and Operations Research, vol. 10, no. 4, pp. 335–343, 1983. View at Google Scholar · View at Scopus
  5. K. Wise and D. E. Perushek, “Linear goal programming for academic library acquisitions allocations,” Library Acquisitions: Practice and Theory, vol. 20, no. 3, pp. 311–327, 1996. View at Google Scholar · View at Scopus
  6. K. Wise and D. E. Perushek, “Goal programming as a solution technique for the acquisitions allocation problem,” Library and Information Science Research, vol. 22, no. 2, pp. 165–183, 2000. View at Google Scholar · View at Scopus
  7. T.-F. Ho, S. J. Shyu, B. M. T. Lin, and Y.-L. Wu, “An evolutionary approach to library materials acquisition problems,” in Proceedings of the IEEE International Conference on Intelligent Systems (IS '10), pp. 450–455, London, UK, July 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. S. K. Goyal, “Allocation of library funds to different departments of a university—an operational research approach,” College and Research Libraries, vol. 34, pp. 219–222, 1973. View at Google Scholar
  9. A. Arora and D. Klabjan, “A model for budget allocation in multi-unit libraries,” Library Collections, Acquisition and Technical Services, vol. 26, no. 4, pp. 423–438, 2002. View at Publisher · View at Google Scholar · View at Scopus
  10. T. Niyonsenga and B. Bizimana, “Measures of library use and user satisfaction with academic library services,” Library and Information Science Research, vol. 18, no. 3, pp. 225–240, 1996. View at Publisher · View at Google Scholar · View at Scopus
  11. M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freemaan and Company, New York, NY, USA, 1979.
  12. C.-J. Liao, C.-T. Tseng, and P. Luarn, “A discrete version of particle swarm optimization for flowshop scheduling problems,” Computers and Operations Research, vol. 34, no. 10, pp. 3099–3111, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. T. J. Ai and V. Kachitvichyanukul, “A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery,” Computers and Operations Research, vol. 36, no. 5, pp. 1693–1702, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, Perth, Australia, December 1995. View at Scopus
  15. R. Poli, “Analysis of the publications on the applications of particle swarm optimisation,” Journal of Artificial Evolution and Applications, vol. 2008, Article ID 685175, 10 pages, 2008. View at Publisher · View at Google Scholar
  16. A. Silva, A. Neves, and T. Goncalves, “An heterogeneous particle swarm optimizer with predator and scout particles,” in Autonomous and Intelligent Systems, Lecture Notes in Computer Science, pp. 200–208, 2012. View at Google Scholar
  17. A. Hatamlou, “Black hole: a new heuristic optimization approach for data clustering,” Information Science, vol. 222, pp. 175–184, 2013. View at Google Scholar
  18. C.-C. Chiu, M.-H. Ho, and S.-H. Liao, “PSO and APSO for optimizing coverage in indoor UWB communication system,” International Journal of RF and Microwave Computer-Aided Engineering, vol. 23, no. 3, pp. 300–308, 2013. View at Google Scholar
  19. Y. Tian, D. Liu, D. Yuan, and K. Wang, “A discrete PSO for two-stage assembly scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 66, no. 1-4, pp. 481–499, 2013. View at Google Scholar
  20. J. Kennedy and R. C. Eberhart, “Discrete binary version of the particle swarm algorithm,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 4104–4108, Piscataway, NJ, USA, October 1997. View at Scopus
  21. R. C. Eberhart and Y. Shi, “Comparing inertia weights and constriction factors in particle swarm optimization,” in Proceedings of the Congress on Evolutionary Computation (CEC '00), pp. 84–88, La Jolla, Calif, USA, July 2000. View at Scopus
  22. R. Poli, J. Kennedy, and T. Blackwell, “Particle swarm optimization: an overview,” Swarm Intelligence, vol. 1, pp. 33–57, 2007. View at Google Scholar
  23. D. Bratton and J. Kennedy, “Defining a standard for particle swarm optimization,” in Proceedings of the IEEE Swarm Intelligence Symposium (SIS '07), pp. 120–127, Honolulu, Hawaii, USA, April 2007. View at Publisher · View at Google Scholar · View at Scopus
  24. G. Coath and S. K. Halgamuge, “A comparison of constraint-handling methods for the application of particle swarm optimization to constrained nonlinear optimization problems,” in Proceedings of the Congress on Evolutionary Computation, pp. 2419–2425, Canberra, Australia, December 2003.
  25. K. E. Parsopoulos and M. N. Vrahatis, “Particle swarm optimization method for constrained optimization problems,” in Intelligent Technologies—Theory and Applications: New Trends in Intelligent Technologies, vol. 76, pp. 214–220, 2002. View at Google Scholar
  26. G. T. Pulido and C. A. Coello Coello, “A constraint-handling mechanism for particle swarm optimization,” in Proceedings of the Congress on Evolutionary Computation (CEC '04), pp. 1396–1403, Portland, Ore, USA, June 2004. View at Scopus
  27. A. García-Villoria and R. Pastor, “Introducing dynamic diversity into a discrete particle swarm optimization,” Computers and Operations Research, vol. 36, no. 3, pp. 951–966, 2009. View at Publisher · View at Google Scholar · View at Scopus
  28. T. M. Blackwell and P. Bentley, “Don’t push me! Collision-avoiding swarms,” in Proceedings of the Congress on Evolutionary Computation, pp. 1691–1696, Honolulu, Hawaii, USA, May 2002.
  29. Y.-L. Wu, T.-F. Ho, S. J. Shyu, and B. M. T. Lin, “Discrete particle swarm optimization for materials acquisition in multi-unit libraries,” in Proceedings of the Congress on Evolutionary Computation, pp. 1–7, Brisbane, Australia, June 2012.