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Using Resource Scarceness Characteristics to Solve the Multi-Mode Resource-Constrained Project Scheduling Problem

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Author Info
V. VAN PETEGHEM ()
M. VANHOUCKE ()

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Abstract

In the past decades, resource parameters have been introduced in project scheduling literature to measure the scarceness of resources of a project instance. In this paper, we use these resource scarceness parameters to di erentiate in the search process needed to solve the multi-mode resource constrained project scheduling problem, in which multiple execution modes are available for each activity in the project. Therefore, we propose a scatter search algorithm, which is executed with di erent improvement methods, each tailored to the speci c characteristics of di erent renewable and nonrenewable resource scarceness values. Computational results prove the e ectiveness of the improvement methods and reveal that the procedure is among the most competitive algorithms in the open literature.

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Publisher Info
Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 09/595.

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Length: 21 pages
Date of creation: Jun 2009
Date of revision:
Handle: RePEc:rug:rugwps:09/595

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Related research
Keywords: project scheduling; scatter search; multi-mode RCPSP; resource scarceness matrix;

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  1. Mori, Masao & Tseng, Ching Chih, 1997. "A genetic algorithm for multi-mode resource constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 100(1), pages 134-141, July. [Downloadable!] (restricted)
  2. Vanhoucke, Mario & Coelho, Jose & Debels, Dieter & Maenhout, Broos & Tavares, Luis V., 2008. "An evaluation of the adequacy of project network generators with systematically sampled networks," European Journal of Operational Research, Elsevier, vol. 187(2), pages 511-524, June. [Downloadable!] (restricted)
  3. Brucker, Peter & Drexl, Andreas & Mohring, Rolf & Neumann, Klaus & Pesch, Erwin, 1999. "Resource-constrained project scheduling: Notation, classification, models, and methods," European Journal of Operational Research, Elsevier, vol. 112(1), pages 3-41, January. [Downloadable!] (restricted)
  4. Marti, Rafael & Laguna, Manuel & Glover, Fred, 2006. "Principles of scatter search," European Journal of Operational Research, Elsevier, vol. 169(2), pages 359-372, March. [Downloadable!] (restricted)
  5. Bouleimen, K. & Lecocq, H., 2003. "A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version," European Journal of Operational Research, Elsevier, vol. 149(2), pages 268-281, September. [Downloadable!] (restricted)
  6. Ozdamar, Linet & Ulusoy, Gunduz, 1994. "A local constraint based analysis approach to project scheduling under general resource constraints," European Journal of Operational Research, Elsevier, vol. 79(2), pages 287-298, December. [Downloadable!] (restricted)
  7. Lova, Antonio & Tormos, Pilar & Cervantes, Mariamar & Barber, Federico, 2009. "An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes," International Journal of Production Economics, Elsevier, vol. 117(2), pages 302-316, February. [Downloadable!] (restricted)
  8. Buddhakulsomsiri, Jirachai & Kim, David S., 2007. "Priority rule-based heuristic for multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting," European Journal of Operational Research, Elsevier, vol. 178(2), pages 374-390, April. [Downloadable!] (restricted)
  9. Boctor, Fayez F., 1996. "A new and efficient heuristic for scheduling projects with resource restrictions and multiple execution modes," European Journal of Operational Research, Elsevier, vol. 90(2), pages 349-361, April. [Downloadable!] (restricted)
  10. 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. [Downloadable!] (restricted)
  11. Pinol, H. & Beasley, J.E., 2006. "Scatter Search and Bionomic Algorithms for the aircraft landing problem," European Journal of Operational Research, Elsevier, vol. 171(2), pages 439-462, June. [Downloadable!] (restricted)
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