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Problem space search algorithms for resource-constrained project scheduling

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  • Kedar Naphade
  • S. David Wu
  • Robert Storer

Abstract

The Resource-Constrained Project Scheduling (RCPS) problem is a well known and challenging combinatorial optimization problem. It is a generalization of the Job Shop Scheduling problem and thus is NP-hard in the strong sense. Problem Space Search is a local search "metaheuristic" which has been shown to be effective for a variety of combinatorial optimization problems including Job Shop Scheduling. In this paper, we propose two problem space search heuristics for the RCPS problem. These heuristics are tested through intensive computational experiments on a 480-instance RCPS data set recently generated by Kolisch et al. [12]. Using this data set we compare our heuristics with a branch-and-bound algorithm developed by Demuelemeester and Herreolen [9]. The results produced by the heuristics are extremely encouraging, showing comparable performance to the branch-and-bound algorithm. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Kedar Naphade & S. David Wu & Robert Storer, 1997. "Problem space search algorithms for resource-constrained project scheduling," Annals of Operations Research, Springer, vol. 70(0), pages 307-326, April.
    • Handle: RePEc:spr:annopr:v:70:y:1997:i:0:p:307-326:10.1023/a:1018982423325
    DOI: 10.1023/A:1018982423325
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    Citations

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    Cited by:

    1. Kolisch, R. & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Omega, Elsevier, vol. 29(3), pages 249-272, June.
    2. Andreas Schirmer, 2000. "Case‐based reasoning and improved adaptive search for project scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(3), pages 201-222, April.
    3. Franz Rothlauf, 2009. "An Encoding in Metaheuristics for the Minimum Communication Spanning Tree Problem," INFORMS Journal on Computing, INFORMS, vol. 21(4), pages 575-584, November.
    4. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
    5. Valls, Vicente & Quintanilla, Sacramento & Ballestin, Francisco, 2003. "Resource-constrained project scheduling: A critical activity reordering heuristic," European Journal of Operational Research, Elsevier, vol. 149(2), pages 282-301, September.
    6. Schirmer, Andreas & Riesenberg, Sven, 1998. "Class-based control schemes for parameterized project scheduling heuristics," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 471, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    7. Xiaowei Lin & Jing Zhou & Lianmin Zhang & Yinlian Zeng, 2021. "Revenue sharing for resource reallocation among project activity contractors," Annals of Operations Research, Springer, vol. 301(1), pages 121-141, June.
    8. Jeet, V. & Kutanoglu, E., 2007. "Lagrangian relaxation guided problem space search heuristics for generalized assignment problems," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1039-1056, November.
    9. Neumann, K. & Schwindt, C. & Zimmermann, J., 2003. "Order-based neighborhoods for project scheduling with nonregular objective functions," European Journal of Operational Research, Elsevier, vol. 149(2), pages 325-343, September.
    10. Hartmann, Sonke & Kolisch, Rainer, 2000. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 127(2), pages 394-407, December.
    11. Kolisch, Rainer & Hartmann, Sönke, 1998. "Heuristic algorithms for solving the resource-constrained project scheduling problem: Classification and computational analysis," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 469, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    12. Schirmer, Andreas, 1998. "Case-based reasoning and improved adaptive search for project scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 472, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    13. Hartmann, Sönke & Kolisch, Rainer, 1998. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 476, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. Fleszar, Krzysztof & Hindi, Khalil S., 2004. "Solving the resource-constrained project scheduling problem by a variable neighbourhood search," European Journal of Operational Research, Elsevier, vol. 155(2), pages 402-413, June.

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