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A Scatter Search Hybrid Algorithm for Resource Availability Cost Problem

  • Hexia Meng
  • Bing Wang
  • Yabing Nie
  • Xuedong Xia
  • Xianxia Zhang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 382)

Abstract

This paper discusses the resource availability cost problem (RACP) with the objective of minimizing the total cost of the unlimited renewable resources by a prespecified project deadline. A tabued scatter search (TSS) algorithm is developed to solve the RACP. The deadline constraint is handled in coding. A tabu search module is embedded in the framework of scatter search. A computational experiment was conducted and the computational results show that the proposed TSS hybrid algorithm is effective and advantageous for the RACP.

Keywords

RACP Scatter search Tabu search 

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References

  1. 1.
    Blazewicz, J., Lenstra, J.K., Rinnooy Kan, A.H.G.: Scheduling subject to resource constraints: Classification and complexity. Discrete Appl. Math. 5, 13–24 (1983)Google Scholar
  2. 2.
    Herroelen, W., De Reyck, B., Demeulemeester, E.: Resource-constrained project scheduling: A survey of recent developments. Comput. Oper. Res. 25, 279–302 (1998)zbMATHMathSciNetCrossRefGoogle Scholar
  3. 3.
    Kolisch, R., Hartmann, S.: Heuristic algorithms for the resource-constrained project scheduling problem: classification and computational analysis. In: Weglarz, J. (ed.) Project Scheduling: Recent Models, Algorithms, and Applications, pp. 147–178. Kluwer Academic Publishers (1998)Google Scholar
  4. 4.
    Kolisch, R., Hartmann, S.: Experimental investigation of heuristics for resource-constrained project scheduling: An update. Eur. J. Oper. Res 174, 23–37 (2006)zbMATHCrossRefGoogle Scholar
  5. 5.
    Al-Fawzan, M.A., Haouari, M.: A bi-objective model for robust resource-constrained project scheduling. Int. J. Prod. Econ. 96, 175–187 (2005)CrossRefGoogle Scholar
  6. 6.
    Lambrechts, O., Demeulemeester, E., Herroelen, W.: A tabu search procedure for developing robust predictive project schedules. Int. J. Prod. Econ. 111, 493–508 (2008)CrossRefGoogle Scholar
  7. 7.
    Möhring, R.H.: Minimizing costs of resource requirements in project networks subject to a fix completion time. Oper. Res. 32, 89–120 (1984)zbMATHCrossRefGoogle Scholar
  8. 8.
    Van Peteghem, V., Vanhoucke, M.: An artificial immune system algorithm for the resource availability cost problem. Flexible Int. J. Flexible Manuf. Syst. 25, 122–144 (2013)Google Scholar
  9. 9.
    Demeulemeester, E.: Minimizing resource availability costs in time-limited project networks. Manage. Sci. 41, 1590–1598 (1995)zbMATHCrossRefGoogle Scholar
  10. 10.
    Rangaswamy, B.: Multiple Resource Planning and Allocation in Resource-Constrained Project Networks. University of Colorado, Colorado (1998)Google Scholar
  11. 11.
    Rodrigues, S.B., Yamashita, D.S.: An exact algorithm for minimizing resource availability costs in project scheduling. Eur. J. Oper. Res. 206, 562–568 (2010)zbMATHMathSciNetCrossRefGoogle Scholar
  12. 12.
    Drexl, A., Kimms, A.: Optimization guided lower and upper bounds for the resource investment problem. J. Oper. Res. Soc. 52, 340–351 (2001)zbMATHCrossRefGoogle Scholar
  13. 13.
    Shadrokh, S., Kianfar, F.: A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty. Eur. J. Oper. Res. 181, 86–101 (2007)zbMATHMathSciNetCrossRefGoogle Scholar
  14. 14.
    Yamashita, D.S., Armentano, V.A., Laguna, M.: Scatter search for project scheduling with resource availability cost. Eur. J. Oper. Res. 169, 623–637 (2006)zbMATHMathSciNetCrossRefGoogle Scholar
  15. 15.
    Yamashita, D.S., Armentano, V.A., Laguna, M.: Robust optimization models for project scheduling with resource availability cost. J. Sched. 12, 67–76 (2007)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Qi, J.J., Guo, B., Lei, H.T., Zhang, T.: Solving resource availability cost problem in project scheduling by pseudo particle swarm optimization. J. Syst. Eng. Electron. 25, 69–76 (2014)CrossRefGoogle Scholar
  17. 17.
    Ranjbar, M., Kianfar, F., Shadrokh, S.: Solving the resource availability cost problem in project scheduling by path relinking and genetic algorithm. Appl. Math. Comput. 196, 879–888 (2008)zbMATHMathSciNetCrossRefGoogle Scholar
  18. 18.
    Shaffer, L.R., Ritter, J.B., Meyer, W.L.: The critical-path method. McGraw-Hill, New York (1965)Google Scholar
  19. 19.
    Glover, F.: Heuristics for integer programming using surrogate constraints. Decision Sci. 8, 156–166 (1977)CrossRefGoogle Scholar
  20. 20.
    Glover, F.: A template for scatter search and path relinking. In: Hao, J.-K., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds.) AE 1997. LNCS, vol. 1363, pp. 1–51. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  21. 21.
    Martí, R., Laguna, M., Glover, F.: Principles of Scatter Search. Eur. J. Oper. Res. 169, 359–372 (2006)zbMATHCrossRefGoogle Scholar
  22. 22.
    Glover, F.: Future paths for integer programming and links to artificial intelligence. Comput. Oper. Res. 13, 533–549 (1986)zbMATHMathSciNetCrossRefGoogle Scholar
  23. 23.
    Kolisch, R., Sprecher, A., Drexl, A.: Characterization and generation of a general class of resource-constrained project scheduling problems. Manage. Sci. 41, 1693–1703 (1995)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Hexia Meng
    • 1
  • Bing Wang
    • 1
  • Yabing Nie
    • 1
  • Xuedong Xia
    • 1
  • Xianxia Zhang
    • 1
  1. 1.School of Mechatronic Engineering and AutomationShanghai UniversityShanghaiChina

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