Advertisement

Solution of a Modified Balanced Academic Curriculum Problem Using Evolutionary Strategies

  • Lorna V. Rosas-Tellez
  • Vittorio Zanella-Palacios
  • Jose L. Martínez-Flores
Part of the Studies in Computational Intelligence book series (SCI, volume 465)

Abstract

The Balanced Academic Curriculum Problem (BACP) is a constraint satisfaction problem classified as NP- Hard, this problem consists in the allocation of courses in the periods that are part of a curriculum such that the prerequisites are satisfied and the load of courses is balanced for the students. In this paper is presented the solution for a modified BACP where the loads may be the same or different for each one of the periods and is allowed to have some courses in a specific period. This problem is modeled as an integer programming problem and is proposed the use of evolutionary strategies for its solution because was not possible to find solutions for all the instances of this modified problem with formal methods.

Keywords

Optimization Evolutionary strategies Balanced academic curriculum problem 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Salazar, J.: Programación Matemática, Diaz de Santos, Madrid (2001)Google Scholar
  2. 2.
    Castro, C., Manzano, S.: Variable and value ordering when solving balanced academic curriculum problem. In: Proceedings of the ERCIM Working Group on Constraints (2001)Google Scholar
  3. 3.
    CSPLib: A problem library for constraints, http://www.csplib.org/
  4. 4.
    Lambert, T., Castro, C., Monfroy, E., Saubion, F.: Solving the Balanced Academic Curriculum Problem with an Hybridization of Genetic Algorithm and Constraint Propagation. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 410–419. Springer, Heidelberg (2006)Google Scholar
  5. 5.
    Di Gaspero, L., Schaerf, A.: Hybrid Local Search Techniques for the Generalized Balanced Academic Curriculum Problem. In: Blesa, M.J., Blum, C., Cotta, C., Fernández, A.J., Gallardo, J.E., Roli, A., Sampels, M. (eds.) HM 2008. LNCS, vol. 5296, pp. 146–157. Springer, Heidelberg (2008)Google Scholar
  6. 6.
    Aguilar-Solís, J.A.: Un modelo basado en optimización para balancear planes de estudio en Instituciones de Educación Superior. PhD Thesis. UPAEP, Puebla (2008)Google Scholar
  7. 7.
    Castro, C., Crawford, B., Monfroy, E.: A Genetic Local Search Algorithm for the Multiple Optimisation of the Balanced Academic Curriculum Problem. In: Shi, Y., Wang, S., Peng, Y., Li, J., Zeng, Y. (eds.) MCDM 2009. CCIS, vol. 35, pp. 824–832. Springer, Heidelberg (2009)Google Scholar
  8. 8.
    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lorna V. Rosas-Tellez
    • 1
  • Vittorio Zanella-Palacios
    • 1
  • Jose L. Martínez-Flores
    • 2
  1. 1.Information Technologies DepartmentUniversidad Popular Autónoma del Estado de PueblaPuebla PueMéxico
  2. 2.Interdisciplinary Center for Postgraduate Studies, Research, and ConsultingUniversidad Popular Autónoma del Estado de PueblaPuebla PueMéxico

Personalised recommendations