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Adaptive search for solving hard project scheduling problems

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  • Rainer Kolisch
  • Andreas Drexl

Abstract

In this article we propose a new heuristic solution technique for resource‐constrained project scheduling problems. Basically, it is a hybrid of priority rule and random search techniques which employs two types of adaptations in order to determine the solution space. We enhance this general scheme by the use of a new priority rule and by lower bounding techniques. The method is evaluated by comparing it with other recently proposed heuristics on a widely used set of benchmark‐instances. Furthermore, we show that the procedure can be usefully applied to solve different hard problems within the field of project scheduling. © 1996 John Wiley & Sons, Inc.

Suggested Citation

  • Rainer Kolisch & Andreas Drexl, 1996. "Adaptive search for solving hard project scheduling problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(1), pages 23-40, February.
  • Handle: RePEc:wly:navres:v:43:y:1996:i:1:p:23-40
    DOI: 10.1002/(SICI)1520-6750(199602)43:13.0.CO;2-P
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    References listed on IDEAS

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    Cited by:

    1. André Schnabel & Carolin Kellenbrink & Stefan Helber, 2018. "Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints," Business Research, Springer;German Academic Association for Business Research, vol. 11(2), pages 329-356, September.
    2. Sepehr Proon & Mingzhou Jin, 2011. "A genetic algorithm with neighborhood search for the resource‐constrained project scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 73-82, March.
    3. Sönke Hartmann, 1998. "A competitive genetic algorithm for resource‐constrained project scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(7), pages 733-750, October.
    4. Osman Hürol Türkakın & David Arditi & Ekrem Manisalı, 2021. "Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
    5. 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.
    6. Sönke Hartmann, 2002. "A self‐adapting genetic algorithm for project scheduling under resource constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(5), pages 433-448, August.
    7. Dieter Debels & Mario Vanhoucke, 2007. "A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem," Operations Research, INFORMS, vol. 55(3), pages 457-469, June.

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