Advertisement

An Artificial Bee Colony Algorithm for the Resource Contrained Project Scheduling Problem

  • Broderick Crawford
  • Ricardo Soto
  • Franklin JohnsonEmail author
  • Enrique Norero
  • Eduardo Olguín
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)

Abstract

We present an approach to solve the Resource Constrained Project Scheduling Problem. This problem consists on executing a group of activities limited by constraints. Precedence relationships force to some activities to begin after the finalization of others. In addition, processing every activity requires a predefined amount of limited resources. The target of this problem is to minimize the duration of whole project. In this paper, an approach based on Artificial Bee Colony algorithm for the Resource Constrained Project Scheduling Problem is presented. That algorithm is one of the most recent algorithms in the domain of the collective intelligence who was motivated by the intelligent behavior observed in the domestic bees to take the process of forage. Thus, ABC combines methods of local search and global search, trying to balance the process of the exploration and exploitation of the space of search.

Keywords

Artificial bee colony Metaheuristic Project scheduling 

Notes

Acknowledgments

Broderick Crawford is supported by Grant CONICYT/ FONDECYT/REGULAR/1140897, Ricardo Soto is supported by Grant CONICYT/FONDECYT/INICIACION/11130459, Franklin Johnson is supported by Postgraduate Grant PUCV 2014.

References

  1. 1.
    Bouleimen, K., Lecocq, H.: A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. Eur. J. Oper. Res. 149(2), 268–281 (2003)CrossRefMathSciNetzbMATHGoogle Scholar
  2. 2.
    Chen, R.-M., Wu, C.-L., Wang, C.-M., Lo, S.-T.: Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in psplib. Expert Syst. Appl. 37(3), 1899–1910 (2010)CrossRefGoogle Scholar
  3. 3.
    Chiarandini, M., Di Gaspero, L., Gualandi, S., Schaerf, A.: The balanced academic curriculum problem revisited. J. Heuristics 18(1), 119–148 (2012)CrossRefGoogle Scholar
  4. 4.
    Hartmann, S.: A competitive genetic algorithm for resource-constrained project scheduling. Naval Res. Logistics (NRL) 45(7), 733–750 (1998)CrossRefzbMATHGoogle Scholar
  5. 5.
    Herbots, J., Herroelen, W., Leus, R.: Experimental investigation of the applicability of ant colony optimization algorithms for project scheduling. DTEW Res. Rep. 0459, 1–25 (2004)Google Scholar
  6. 6.
    Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report, Technical report-tr06, Erciyes university, Engineering Faculty, Computer Engineering Department (2005)Google Scholar
  7. 7.
    Kempf, K., Uzsoy, R., Smith, S., Gary, K.: Evaluation and comparison of production schedules. Comput. Ind. 42(2), 203–220 (2000)CrossRefGoogle Scholar
  8. 8.
    Nonobe, K., Ibaraki, T.: Formulation and Tabu search algorithm for the resource constrained project scheduling problem. In: Ribeiro, C.C., Hansen, P. (eds.) Essays and Surveys in Metaheuristics, pp. 557–588. Springer, London (2002)CrossRefGoogle Scholar
  9. 9.
    Schirmer, A.: Case-based reasoning and improved adaptive search for project scheduling. Naval Res. Logistics (NRL) 47(3), 201–222 (2000)CrossRefMathSciNetzbMATHGoogle Scholar
  10. 10.
    Valls, V., Ballestín, F., Quintanilla, S.: Justification and RCPSP: a technique that pays. Eur. J. Oper. Res. 165(2), 375–386 (2005)CrossRefzbMATHGoogle Scholar
  11. 11.
    Zhang, H., Li, H., Tam, C.: Particle swarm optimization for resource-constrained project scheduling. Int. J. Project Manag. 24(1), 83–92 (2006)CrossRefGoogle Scholar
  12. 12.
    Zhang, H., Li, X., Li, H., Huang, F.: Particle swarm optimization-based schemes for resource-constrained project scheduling. Autom. Constr. 14(3), 393–404 (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Broderick Crawford
    • 1
    • 2
    • 3
  • Ricardo Soto
    • 1
    • 4
    • 5
  • Franklin Johnson
    • 1
    • 6
    Email author
  • Enrique Norero
    • 7
  • Eduardo Olguín
    • 3
  1. 1.Pontificia Universidad Católica de ValparaísoValparaísoChile
  2. 2.Universidad Central de ChileSantiagoChile
  3. 3.Universidad San SebastiánSantiagoChile
  4. 4.Universidad Autónoma de ChileSantiagoChile
  5. 5.Universidad Científica del SurLimaPerú
  6. 6.Universidad de Playa AnchaValparaísoChile
  7. 7.Facultad de IngenieríaUniversidad Santo TomásViña del MarChile

Personalised recommendations