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Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

Author

Listed:
  • Yi Han
  • Ikou Kaku
  • Jianhu Cai
  • Yanlai Li
  • Chao Yang
  • Lili Deng

Abstract

This paper presents a shuffled frog leaping algorithm (SFLA) for the single‐mode resource‐constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.

Suggested Citation

  • Yi Han & Ikou Kaku & Jianhu Cai & Yanlai Li & Chao Yang & Lili Deng, 2013. "Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
  • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:451090
    DOI: 10.1155/2013/451090
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    References listed on IDEAS

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    1. Surafel Luleseged Tilahun & Hong Choon Ong, 2012. "Modified Firefly Algorithm," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-12, November.
    2. Lipu Zhang & Yinghong Xu & Yousong Liu, 2012. "An Elite Decision Making Harmony Search Algorithm for Optimization Problem," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-15, July.
    3. Yingcheng Xu & Li Wang & Yuexiang Yang, 2013. "Dynamic Vehicle Routing Using an Improved Variable Neighborhood Search Algorithm," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-12, February.
    4. Kolisch, R. & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Omega, Elsevier, vol. 29(3), pages 249-272, June.
    5. Surafel Luleseged Tilahun & Hong Choon Ong, 2012. "Modified Firefly Algorithm," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
    6. Al-Fawzan, M. A. & Haouari, Mohamed, 2005. "A bi-objective model for robust resource-constrained project scheduling," International Journal of Production Economics, Elsevier, vol. 96(2), pages 175-187, May.
    7. Golenko-Ginzburg, Dimitri & Gonik, Aharon, 1998. "A heuristic for network project scheduling with random activity durations depending on the resource allocation," International Journal of Production Economics, Elsevier, vol. 55(2), pages 149-162, July.
    8. Yingcheng Xu & Li Wang & Yuexiang Yang, 2013. "Dynamic Vehicle Routing Using an Improved Variable Neighborhood Search Algorithm," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    9. Lipu Zhang & Yinghong Xu & Yousong Liu, 2012. "An Elite Decision Making Harmony Search Algorithm for Optimization Problem," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
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