Skip to main content
SpringerLink
Log in

Scenario-Based Evolutionary Approach for Robust RCPSP

  • Conference paper
  • First Online:
Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 427))

  • 987 Accesses

Abstract

The present paper deals with the resource-constrained project scheduling problem with uncertain activity durations. Based on scenarios, we investigate two robust models, the min-max model which focuses on the minimization of the absolute robustness objective and the min-max regret model having the object to minimize the absolute regret. We propose an adaptive robust genetic approach with a sophisticated initial population and a Forward-Backward Improvement heuristic. The proposed algorithm is applied for the PSPLIB J30 data set with modified activity durations. Obtained results show the performance of the genetic algorithm combined with the improvement heuristic compared with the basic version. Different perturbation levels were tested to determine the corresponding performance degradation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Blazewicz, J., Lenstra, J., Rinnooy Kan, A.: Classification and complexity. Discret. Appl. Math. 5, 11–24 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  2. Davenport, A.J., Beck, J.C.: A survey of techniques for scheduling with uncertainty (2000). http://tidel.mie.utoronto.ca/publications.php

  3. Kolisch, R., Hartmann, S.: Heuristic algorithms for the resource-constrained project scheduling problem: classification and computational analysis. In: Weglarz, J. (ed.) Project Scheduling. International Series in Operations Research and Management Science, vol. 14, pp. 147–178. Springer, US (1999)

    Chapter  Google Scholar 

  4. Kolisch, R., Hartmann, S.: Experimental investigation of heuristics for resource-constrained project scheduling: an update. Eur. J. Oper. Res. 174, 23–37 (2006)

    Article  MATH  Google Scholar 

  5. Herroelen, W., Leus, R.: Project scheduling under uncertainty: survey and research potentials. Eur. J. Oper. Res. 165, 289–306 (2005)

    Article  MATH  Google Scholar 

  6. Al-Fawzan, M., Haouari, M.: A bi-objective model for robust resource-constrained project scheduling. Int. J. Prod. Econ. 18, 1–13 (2004)

    Google Scholar 

  7. Abbasi, B., Shadrokh, S., Arkat, J.: Bi-objective resource-constrained project scheduling with robustness and makespan criteria. Appl. Math. Comput. 180(1), 146–152 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  8. Chtourou, H., Haouari, M.: A two-stage-priority-rule-based algorithm for robust resource-constrained project scheduling. Comput. Ind. Eng. 55, 183–194 (2008)

    Article  Google Scholar 

  9. Yamashita, D.S., Armentano, V.A., Laguna, M.: Robust optimization models for project scheduling with resource availability cost. J. Sched. 10, 67–76 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  10. Artigues, C., Leus, R., Talla Nobibon, F.: Robust optimization for resource-constrained project scheduling with uncertain activity durations. Flex. Syst. Manag. J. 25(1–2), 175–205 (2013)

    Google Scholar 

  11. Kouvelis, P., Yu, G.: Robust Discrete Optimiaztion and Its Applications. Klower Academic Publisher (1997)

    Google Scholar 

  12. Sevaux, M., Sorensen, K.: A genetic algorithm for robust schedules. 4OR 2, pp. 129–147 (2004)

    Google Scholar 

  13. Tormos, M.P., Lova, A.L.: A competitive heuristic solution technique for resource-constrained project scheduling. Annals OR, (1–4), 65–81 (2001)

    Google Scholar 

  14. Valls, V., Ballestin, F., Quintanilla, S.: Justification and rcpsp: a technique that pays. Eur. J. Oper. Res. 165, 375–386 (2005)

    Article  MATH  Google Scholar 

  15. Kolisch, R.: Psplib-a project scheduling problem library. Eur. J. Oper. Res. 103, 483–496 (1997)

    Google Scholar 

  16. Ashtiani, B., Leus, R., Aryanezhad, M.B.: A novel class of scheduling policies for the stochastic resource-constrained project scheduling problem. Available at SSRN 1368714 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Engineering School of Tunis, Tunis El Manar University, Tunis, Tunisia

    Hayet Mogaadi & Besma Fayech Chaar

Authors
  1. Hayet Mogaadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Besma Fayech Chaar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hayet Mogaadi .

Editor information

Editors and Affiliations

  1. Sci. Network for Innovation & Rec. Exell, Machine Intelligence Research Labs (MIR, Auburn, Washington, USA

    Ajith Abraham

  2. Membre du Groupe Efrei, ESIGETEL, Villejuif, France

    Katarzyna Wegrzyn-Wolska

  3. Faculty of Computers & Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Mogaadi, H., Chaar, B.F. (2016). Scenario-Based Evolutionary Approach for Robust RCPSP. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015. Advances in Intelligent Systems and Computing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-29504-6_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-29504-6_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29503-9

  • Online ISBN: 978-3-319-29504-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation