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Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements

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  • Arno Sprecher

    (Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre, Lehrstuhl für Produktion und Logistik, Olshausenstra\beta e 40, 24098 Kiel, Germany)

Abstract

We consider the resource-constrained project scheduling problem. The purpose of this paper is to direct the focus to a branch-and-bound concept that can, by simple adaptations, operate on a wide range of problem settings. The general approach can, e.g., deal with multimode problems, resource availability varying with time, and a wide range of objectives. Even the simple assembly line balancing problem of type-1 can be competitively approached with some modifications. Although the algorithm is the most general and simple one currently available for resource-constrained project scheduling, the computational performance can compete with the best approaches available for the single-mode problem. The algorithm uses far less memory than the state-of-the-art procedure, i.e., 256 KB versus 24 MB, for solving the standard benchmark set with projects consisting of 32 activities within comparable time. If both approaches are allowed to make limited use of memory, i.e., 256 KB, then more than 97% of the benchmark instances can be solved within fractions of the time required by the current state-of-the-art procedure. The truncated version of our algorithm achieves at 256 KB approximately the results of the truncated version of the state-of-the-art approach at 24 MB. Since in general the memory requirements exponentially grow with the number of activities the project consists of, memory will become a critical resource, and the strategy to access previously stored information will gain fundamental importance when solving larger projects.

Suggested Citation

  • Arno Sprecher, 2000. "Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements," Management Science, INFORMS, vol. 46(5), pages 710-723, May.
  • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:5:p:710-723
    DOI: 10.1287/mnsc.46.5.710.12044
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Guo, Weikang & Vanhoucke, Mario & Coelho, José, 2023. "A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 579-595.
    3. Kolisch, R. & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Omega, Elsevier, vol. 29(3), pages 249-272, June.
    4. Dayal Madhukar & Verma, Sanjay, 2015. "Multi-processor Exact Procedures for Regular Measures of the Multi-mode RCPSP," IIMA Working Papers WP2015-03-25, Indian Institute of Management Ahmedabad, Research and Publication Department.
    5. Amadeu A. Coco & Christophe Duhamel & Andréa Cynthia Santos, 2020. "Modeling and solving the multi-period disruptions scheduling problem on urban networks," Annals of Operations Research, Springer, vol. 285(1), pages 427-443, February.
    6. Abdollah Arasteh, 2020. "Considering Project Management Activities for Engineering Design Groups," SN Operations Research Forum, Springer, vol. 1(4), pages 1-29, December.
    7. Debels, Dieter & De Reyck, Bert & Leus, Roel & Vanhoucke, Mario, 2006. "A hybrid scatter search/electromagnetism meta-heuristic for project scheduling," European Journal of Operational Research, Elsevier, vol. 169(2), pages 638-653, March.
    8. Hartmann, Sönke, 2011. "Project scheduling with resource capacities and requests varying with time," Working Paper Series 01/2011, Hamburg School of Business Administration (HSBA).
    9. Andrei Horbach, 2010. "A Boolean satisfiability approach to the resource-constrained project scheduling problem," Annals of Operations Research, Springer, vol. 181(1), pages 89-107, December.
    10. Sophie Demassey & Christian Artigues & Philippe Michelon, 2005. "Constraint-Propagation-Based Cutting Planes: An Application to the Resource-Constrained Project Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 17(1), pages 52-65, February.
    11. 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.
    12. 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.
    13. Salim Rostami & Stefan Creemers & Roel Leus, 2018. "New strategies for stochastic resource-constrained project scheduling," Journal of Scheduling, Springer, vol. 21(3), pages 349-365, June.
    14. D. Debels & M. Vanhoucke, 2005. "A Decomposition-Based Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/293, Ghent University, Faculty of Economics and Business Administration.
    15. Bagloee, Saeed Asadi & Asadi, Mohsen, 2015. "Prioritizing road extension projects with interdependent benefits under time constraint," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 196-216.
    16. Aidin Delgoshaei & Timon Rabczuk & Ahad Ali & Mohd Khairol Anuar Ariffin, 2017. "An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources," Annals of Operations Research, Springer, vol. 259(1), pages 85-117, December.
    17. Chen, Jiaqiong & Askin, Ronald G., 2009. "Project selection, scheduling and resource allocation with time dependent returns," European Journal of Operational Research, Elsevier, vol. 193(1), pages 23-34, February.

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