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Discrete Dynamics in Nature and Society
Volume 2015 (2015), Article ID 841637, 6 pages
http://dx.doi.org/10.1155/2015/841637
Research Article

A Hybrid Heuristic Algorithm for Ship Block Construction Space Scheduling Problem

1School of Economics and Management, Harbin Institute of Technology, Weihai 264209, China
2Department of Mathematics, Harbin Institute of Technology, Weihai 264209, China
3School of Software, Sun Yat-sen University, Guangzhou 510275, China

Received 27 December 2014; Accepted 17 January 2015

Academic Editor: Shuenn-Ren Cheng

Copyright © 2015 Shicheng Hu 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. R. Kolisch, “Efficient priority rules for the resource-constrained project scheduling problem,” Journal of Operations Management, vol. 14, no. 3, pp. 179–192, 1996. View at Publisher · View at Google Scholar · View at Scopus
  2. S. Hartmann, “A competitive genetic algorithm for resource-constrained project scheduling,” Naval Research Logistics, vol. 45, no. 7, pp. 733–750, 1998. View at Google Scholar · View at MathSciNet
  3. Y. Q. Yin, T. C. E. Cheng, X. Q. Yang, and C.-C. Wu, “Two-agent single-machine scheduling with unrestricted due date assignment,” Computers & Industrial Engineering, vol. 79, pp. 148–155, 2015. View at Publisher · View at Google Scholar
  4. Y. Yin, S. R. Cheng, and C. C. Wu, “Parallel-machine scheduling to minimize flowtime, holding, and batch delivery costs,” Asia-Pacific Journal of Operational Research, vol. 31, no. 6, Article ID 1450044, 17 pages, 2014. View at Publisher · View at Google Scholar · View at MathSciNet
  5. E. L. Demeulemeester and W. S. Herroelen, “New benchmark results for the resource-constrained project scheduling problem,” Management Science, vol. 43, no. 11, pp. 1485–1492, 1997. View at Publisher · View at Google Scholar · View at Scopus
  6. P. Raj, “Solving spatial scheduling problem: an analytical approach,” in Proceedings of the 37th International Conference on Computers and Industrial Engineering, pp. 2002–2011, 2007.
  7. J. E. Kelley, “The critical-path method: resources planning and scheduling,” Industrial Scheduling, vol. 13, pp. 347–365, 1963. View at Google Scholar
  8. Z. Liu and H. Wang, “Heuristic algorithm for RCPSP with the objective of minimizing activities' cost,” Journal of Systems Engineering and Electronics, vol. 17, no. 1, pp. 96–102, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. T. Bhaskar, M. N. Pal, and A. K. Pal, “A heuristic method for RCPSP with fuzzy activity times,” European Journal of Operational Research, vol. 208, no. 1, pp. 57–66, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  10. K. J. Lee, J. K. Lee, and S. Y. Choi, “A spatial scheduling system and its application to shipbuilding: DAS-CURVE,” Expert Systems with Applications, vol. 10, no. 3-4, pp. 311–324, 1996. View at Publisher · View at Google Scholar · View at Scopus
  11. S. Koh, R. Logendran, D. Choi, and S. Woo, “Spatial scheduling for shape-changing mega-blocks in a shipbuilding company,” International Journal of Production Research, vol. 49, no. 23, pp. 7135–7149, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. B. S. Baker, E. G. Coffman Jr., and R. L. Rivest, “Orthogonal packings in two dimensions,” SIAM Journal on Computing, vol. 9, no. 4, pp. 846–855, 1980. View at Publisher · View at Google Scholar · View at MathSciNet
  13. B. Chazelle, “bottom-left bin packing heuristic: an efficient implementation,” IEEE Transactions on Computers, vol. 32, no. 8, pp. 697–707, 1983. View at Publisher · View at Google Scholar · View at Scopus
  14. G. Belov, G. Scheithauer, and E. A. Mukhacheva, “One-dimensional heuristics adapted for two-dimensional rectangular strip packing,” Journal of the Operational Research Society, vol. 59, no. 6, pp. 823–832, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. T. M. Chan, F. Alvelos, E. Silva, and J. M. V. de Carvalho, “Heuristics with stochastic neighborhood structures for two-dimensional bin packing and cutting stock problems,” Asia-Pacific Journal of Operational Research, vol. 28, no. 2, pp. 255–278, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. S. Martello, D. Pisinger, and D. Vigo, “The three-dimensional bin packing problem,” Operations Research, vol. 48, no. 2, pp. 256–267, 2000. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. R. Alvarez-Valdes, F. Parreño, and J. M. Tamarit, “A GRASP/Path relinking algorithm for two- and three-dimensional multiple bin-size bin packing problems,” Computers and Operations Research, vol. 40, no. 12, pp. 3081–3090, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. C.-S. Liao and C.-H. Hsu, “New lower bounds for the three-dimensional orthogonal bin packing problem,” European Journal of Operational Research, vol. 225, no. 2, pp. 244–252, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. M. Kucuk and M. Ermis, “A new hybrid evolutionary algorithm for three-dimensional packing problems,” in Proceedings of the IEEE International Conference on Systems Man and Cybernetics (SMC '10), pp. 4029–4034, IEEE, Istanbul, Turkey, October 2010. View at Publisher · View at Google Scholar
  20. M. Steinbrunn, G. Moerkotte, and A. Kemper, “Heuristic and randomized optimization for the join ordering problem,” VLDB Journal, vol. 6, no. 3, pp. 191–208, 1997. View at Publisher · View at Google Scholar · View at Scopus
  21. S. Kirkpatrick, J. Gelatt, and M. P. Vecchi, “Optimization by simulated annealing,” Science, vol. 220, no. 4598, pp. 671–680, 1983. View at Publisher · View at Google Scholar · View at MathSciNet
  22. F. T. S. Chan, A. Prakash, H. L. Ma, and C. S. Wong, “A hybrid Tabu sample-sort simulated annealing approach for solving distributed scheduling problem,” International Journal of Production Research, vol. 51, no. 9, pp. 2602–2619, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. K. Bouleimen and H. Lecocq, “A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version,” European Journal of Operational Research, vol. 149, no. 2, pp. 268–281, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. V. Yannibelli and A. Amandi, “Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem,” Expert Systems with Applications, vol. 40, no. 7, pp. 2421–2434, 2013. View at Publisher · View at Google Scholar · View at Scopus