Skip to main content

Hybrid Heuristics for Dynamic Resource-Constrained Project Scheduling Problem

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6373))

Abstract

Dynamic Resource-Constrained Project Scheduling Problem (DRCPSP) is a scheduling problem that works with an uncommon kind of resources: the Dynamic Resources. They increase and decrease in quantity according to the activated tasks and are not bounded like other project scheduling problems. This paper presents a new mathematical formulation for DRCPSP as well as two hybrid heuristics merging an evolutionary algorithm with an exact approach. Computational results show that both hybrid heuristics present better results than the state-of-the-art algorithm for DRCPSP does. The proposed formulation also provides better bounds.

This work was partially supported by CNPq - grant 141074/2007-8.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chen, P.-H., Shahandashti, S.M.: Hybrid of genetic algorithm and simulated annealing for multiple project scheduling with multiple resource constraints. Autom. in Constr. 18, 434–443 (2009)

    Article  Google Scholar 

  2. Damak, N., Jarboui, B., Siarry, P., Loukil, T.: Differential evolution for solving multi-mode resource-constrained project scheduling problems. Comput. & Oper. Res. 36, 2653–2659 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  3. Fischetti, M., Lodi, A.: Local Branching. Mat. Prog. 98, 23–47 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  4. Fischetti, M., Lodi, A.: Repairing MIP infeasibility through local branching. Comp. & Oper. Res. 35, 1436–1445 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  5. Gonçalves, J., Mendes, J., Resende, M.: A random key based genetic algorithm for the resource constrained project scheduling problems. Int. J. of Prod. Res. 36, 92–109 (2009)

    MathSciNet  MATH  Google Scholar 

  6. Homberger, J.: A multi-agent system for the decentralized resource-constrained multi-project scheduling problem. Int. Trans. in Oper. Res. 14, 565–589 (2007)

    Article  MATH  Google Scholar 

  7. Puchinger, J., Raidl, G.R.: An Evolutionary Algorithm for Column Generation in Integer Programming: an Effective. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 642–651. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Ribeiro, C.C., Rosseti, I.: Efficient Parallel Cooperative Implementations of GRASP Heuristics. Paral. Comp. 33, 21–35 (2007)

    Article  MathSciNet  Google Scholar 

  9. Semet, Y., Schoenauer, M.: An efficient memetic, permutation-based evolutionary algorithm for real-world train timetabling. In: Congress on Evolutionary Computation. IEEE Press, Los Alamitos (2005)

    Google Scholar 

  10. Silva, A.R.V., Ochi, L.S.: A dynamic resource constrained task scheduling problem. In: Proc. of Lat.-Ibero-Am. Congr. on Oper. Res. (CLAIO), Montevideo, Uruguay (November 2006)

    Google Scholar 

  11. Silva, A.R.V., Ochi, L.S.: A hybrid evolutionary algorithm for the dynamic resource constrained task scheduling problem. In: Proc. of the Int. Workshop on Nat. Inspired Distributed Comput. (NIDISC 2007), LongBeach, EUA (March 2007)

    Google Scholar 

  12. Silva, A.R.V., Ochi, L.S., Santos, H.G.: New effective algorithm for dynamic resource constrained project scheduling problem. In: Proc. of Int. Conf. on Eng. Optim. (ENGOPT), Rio de Janeiro, Brazil (June 2008)

    Google Scholar 

  13. Silva, A.R.V., Ochi, L.S.: New sequential and parallel algorithm for dynamic resource constrained project scheduling problem. In: Proc. of Int. Workshop on Nat. Inspired Distributed Comput. (NIDISC 2009), Rome, Italy (May 2009)

    Google Scholar 

  14. Till, J., Sand, G., Urselmann, M., Engell, S.: A hybrid evolutionary algorithm for solving two-stage stochastic integer programs in chemical batch scheduling. Computers & Chemical Engineering 5, 630–647 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

da Silva, A.R.V., Ochi, L.S. (2010). Hybrid Heuristics for Dynamic Resource-Constrained Project Scheduling Problem . In: Blesa, M.J., Blum, C., Raidl, G., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2010. Lecture Notes in Computer Science, vol 6373. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16054-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16054-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16053-0

  • Online ISBN: 978-3-642-16054-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics