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

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  • 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 differentiate 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 different improvement methods, each tailored to the specific characteristics of different renewable and nonrenewable resource scarceness values. Computational results prove the effectiveness of the improvement methods and reveal that the procedure is among the most competitive algorithms in the open literature.

Suggested Citation

  • V. Van Peteghem & M. Vanhoucke, 2009. "Using Resource Scarceness Characteristics to Solve the Multi-Mode Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/595, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:09/595
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    File URL: http://wps-feb.ugent.be/Papers/wp_09_595.pdf
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    References listed on IDEAS

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    1. Marti, Rafael & Laguna, Manuel & Glover, Fred, 2006. "Principles of scatter search," European Journal of Operational Research, Elsevier, vol. 169(2), pages 359-372, March.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Dale F. Cooper, 1976. "Heuristics for Scheduling Resource-Constrained Projects: An Experimental Investigation," Management Science, INFORMS, vol. 22(11), pages 1186-1194, July.
    7. 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.
    8. Rainer Kolisch & Arno Sprecher & Andreas Drexl, 1995. "Characterization and Generation of a General Class of Resource-Constrained Project Scheduling Problems," Management Science, INFORMS, vol. 41(10), pages 1693-1703, October.
    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.
    10. 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.
    11. Arno Sprecher, 2000. "Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements," Management Science, INFORMS, vol. 46(5), pages 710-723, May.
    12. 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.
    13. Kolisch, Rainer & Sprecher, Arno, 1996. "PSPLIB - a project scheduling problem library," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 396, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. 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.
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    1. repec:spr:topjnl:v:25:y:2017:i:1:d:10.1007_s11750-016-0415-2 is not listed on IDEAS
    2. Van Peteghem, Vincent & Vanhoucke, Mario, 2014. "An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances," European Journal of Operational Research, Elsevier, vol. 235(1), pages 62-72.

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    Keywords

    project scheduling; scatter search; multi-mode RCPSP; resource scarceness matrix;

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