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Class-based control schemes for parameterized project scheduling heuristics

Author

Listed:
  • Schirmer, Andreas
  • Riesenberg, Sven
Abstract
Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule-based methods still constitute the most important class of these heuristics. Of these, in turn, parameterized biased random sampling methods have attracted particular interest, due to the fact that they outperform all other priority rule-based methods known. Yet, even the 'best' such algorithms are unable to relate to the particularities of all possible instances of the problem at hand: usually there will exist instances on which other, e.g. the second- or third-best, algorithms perform better. We maintain that asking for the one best algorithm for a given problem may in fact be asking too much. The recently proposed concept of control schemes, which refers to algorithmic schemes allowing to guide the proceeding of parameterized algorithms, opens up ways to refine existing algorithms in this regard. By partitioning the set of all instances of a problem into equivalence classes and identifying algorithmic components that are suited for the respective classes, class-based control schemes constitute one way to achieve this goal. Using the resource-constrained project scheduling problem as a vehicle, we describe how to devise such control schemes, making systematic use of different scheduling schemes as well as random sampling schemes and priority rules. Results from extensive computational experimentation validate effectiveness and efficiency of our approach.

Suggested Citation

  • 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.
    • Handle: RePEc:zbw:cauman:471
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    References listed on IDEAS

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    Cited by:

    1. Messelis, Tommy & De Causmaecker, Patrick, 2014. "An automatic algorithm selection approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 233(3), pages 511-528.
    2. Schirmer, Armin, 1998. "Adaptive control schemes for parameterized heuristic scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 488, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    3. 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.
    4. Schirmer, Andreas, 1999. "Fast iterative improvement methods for project scheduling under partially renewable resources," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 501, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    5. 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.
    6. Schirmer, Andreas, 1999. "Adaptive control schemes applied to project scheduling with partially renewable resources," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 520, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

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