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Integrated Column Generation and Lagrangian Relaxation Approach for the Multi-Skill Project Scheduling Problem

In: Handbook on Project Management and Scheduling Vol.1

Author

Listed:
  • Carlos Montoya

    (Universidad de los Andes)

  • Odile Bellenguez-Morineau

    (IRCCyN, Ecole des Mines de Nantes)

  • Eric Pinson

    (LARIS (EA CNRS 4094), Université Catholique de l’Ouest)

  • David Rivreau

    (LARIS (EA CNRS 4094), Université Catholique de l’Ouest)

Abstract

This chapter introduces a procedure to solve the Multi-Skill Project Scheduling Problem. The problem combines both the classical Resource-Constrained Project Scheduling Problem and the multi-purpose machine model. The aim is to find a schedule that minimizes the completion time (makespan) of a project composed of a set of activities. Precedence relations and resources constraints are considered. In this problem, resources are staff members that master several skills. Thus, a given number of workers must be assigned to perform each skill required by an activity. Practical applications include the construction of buildings, as well as production and software development planning. We present an approach that integrates the utilization of Lagrangian relaxation and column generation for obtaining strong makespan lower bounds. Finally, we present the corresponding obtained results.

Suggested Citation

  • Carlos Montoya & Odile Bellenguez-Morineau & Eric Pinson & David Rivreau, 2015. "Integrated Column Generation and Lagrangian Relaxation Approach for the Multi-Skill Project Scheduling Problem," International Handbooks on Information Systems, in: Christoph Schwindt & Jürgen Zimmermann (ed.), Handbook on Project Management and Scheduling Vol.1, edition 127, chapter 0, pages 565-586, Springer.
    • Handle: RePEc:spr:ihichp:978-3-319-05443-8_26
    DOI: 10.1007/978-3-319-05443-8_26
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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.

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