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An efficient metaheuristic for integrated scheduling and staffing IT projects based on a generalized minimum cost flow network

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  • Rainer Kolisch
  • Christian Heimerl

Abstract

Scheduling IT projects and assigning the project work to human resources are an important and common tasks in almost any IT service company. It is particularly complex because human resources usually have multiple skills. Up to now only little work has considered IT‐specific properties of the project structure and human resources. In this article, we present an optimization model that simultaneously schedules the activities of multiple IT projects with serial network structures and assigns the project work to multiskilled internal and external human resources with different efficiencies. The goal is to minimize costs. We introduce a metaheuristic that decomposes the problem into a binary scheduling problem and a continuous staffing problem where the latter is solved efficiently by exploiting its underlying network structure. For comparison, we solve the mixed–binary linear program with a state–of–the–art commercial solver. The impacts of problem parameters on computation time and solution gaps between the metaheuristic and the solver are assessed in an experimental study. Our results show that the metaheuristic provides very favorable results in considerable less time than the solver for midsize problems. For larger problems, it shows a similar performance while the solver fails to return feasible solutions. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 111–127, 2012

Suggested Citation

  • Rainer Kolisch & Christian Heimerl, 2012. "An efficient metaheuristic for integrated scheduling and staffing IT projects based on a generalized minimum cost flow network," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(2), pages 111-127, March.
  • Handle: RePEc:wly:navres:v:59:y:2012:i:2:p:111-127
    DOI: 10.1002/nav.21476
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    References listed on IDEAS

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    1. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    2. Guidong Zhu & Jonathan F. Bard & Gang Yu, 2006. "A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 18(3), pages 377-390, August.
    3. Neumann, K. & Zimmermann, J., 1999. "Resource levelling for projects with schedule-dependent time windows," European Journal of Operational Research, Elsevier, vol. 117(3), pages 591-605, September.
    4. Jens Brunner & Jonathan Bard & Rainer Kolisch, 2011. "Midterm scheduling of physicians with flexible shifts using branch and price," IISE Transactions, Taylor & Francis Journals, vol. 43(2), pages 84-109.
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    Cited by:

    1. Hartmann, Sönke & Briskorn, Dirk, 2022. "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 1-14.
    2. Snauwaert, Jakob & Vanhoucke, Mario, 2023. "A classification and new benchmark instances for the multi-skilled resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 307(1), pages 1-19.
    3. Meya Haroune & Cheikh Dhib & Emmanuel Neron & Ameur Soukhal & Hafed Mohamed Babou & Mohamedade Farouk Nanne, 2023. "Multi-project scheduling problem under shared multi-skill resource constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 194-235, April.
    4. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.
    5. Thomas Felberbauer & Walter J. Gutjahr & Karl F. Doerner, 2019. "Stochastic project management: multiple projects with multi-skilled human resources," Journal of Scheduling, Springer, vol. 22(3), pages 271-288, June.

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