Office-Space-Allocation Problem Using Harmony Search Algorithm

  • Mohammed A. Awadallah
  • Ahamad Tajudin Khader
  • Mohammed Azmi Al-Betar
  • Phuah Chea Woon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)


Office-Space-Allocation problem is a distribution of a set of limited spaces to a set of resources subject to two types of constraints: hard and soft. Hard constraints must be fulfilled while the soft constraints to be satisfied as much as possible. The quality of the solution is determined based on satisfaction of the soft constraints and the best usage of spaces. The harmony search algorithm (HSA) is a population-based metaheuristic inspired by a musical improvisation process. At each iteration, three operators are used to generate the new harmony: memory consideration, random consideration, and pitch adjustment. In this paper, we modify the memory consideration operator to select from the best solution in the population during the search. HSA is evaluated by using three datasets from Nottingham, and Wolverhampton universities. Experimentally, the HSA obtained new results for two datasets, and a comparable result for the third dataset.


Harmony search Population-based Office-Space-Allocation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Al-Betar, M., Khader, A., Zaman, M.: University Course Timetabling Using a Hybrid Harmony Search Metaheuristic Algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 99, 1–18 (2012)Google Scholar
  2. 2.
    Al-Betar, M., Doush, I., Khader, A., Awadallah, M.: Novel Selection Schemes for Harmony Search. Applied Mathematics and Computation 218(10), 6095–6117 (2011)CrossRefGoogle Scholar
  3. 3.
    Al-Betar, M., Khader, A.: A Harmony Search Algorithm for University Course Timetabling. Annals of Operations Research 94(1), 1–29 (2010)Google Scholar
  4. 4.
    Al-Betar, M., Khader, A., Nadi, F.: Selection Mechanisms in Memory Consideration for Examination Timetabling with Harmony Search. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, pp. 1203–1210. ACM (2010)Google Scholar
  5. 5.
    Awadallah, M., Khader, A., Al-Betar, M., Bolaji, A.: Nurse Scheduling Using Harmony Search. In: 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), pp. 58–63. IEEE (2011)Google Scholar
  6. 6.
    Awadallah, M.A., Khader, A.T., Al-Betar, M.A., Bolaji, A.L.: Nurse Rostering Using Modified Harmony Search Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds.) SEMCCO 2011, Part II. LNCS, vol. 7077, pp. 27–37. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Benjamin, C., Ehie, I., Omurtag, Y.: Planning Facilities at the University of Missouri-rolla. Interfaces, 95–105 (1992)Google Scholar
  8. 8.
    Burke, E.K., Cowling, P., Landa Silva, J.D., McCollum, B.: Three Methods to Automate the Space Allocation Process in UK Universities. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 254–273. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  9. 9.
    Burke, E., Cowling, P., Landa Silva, J.: Hybrid Population-based Metaheuristic Approaches for the Space Allocation Problem. In: Proceedings of the 2001 Congress on Evolutionary Computation, vol. 1, pp. 232–239. IEEE (2001)Google Scholar
  10. 10.
    Corne, D., Ross, P.: Peckish Initialisation Strategies for Evolutionary Timetabling. In: Burke, E.K., Ross, P. (eds.) PATAT 1995. LNCS, vol. 1153, pp. 227–240. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  11. 11.
    Fesanghary, M., Mahdavi, M., Minary-Jolandan, M., Alizadeh, Y.: Hybridizing Harmony Search Algorithm with Sequential Quadratic Programming for Engineering Optimization Problems. Computer Methods in Applied Mechanics and Engineering 197(33-40), 3080–3091 (2008)zbMATHCrossRefGoogle Scholar
  12. 12.
    Geem, Z.: Novel Derivative of Harmony Search Algorithm for Discrete Design Variables. Applied Mathematics and Computation 199(1), 223–230 (2008)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Geem, Z., Kim, J., et al.: A New Heuristic Optimization Algorithm: Harmony Aearch. Simulation 76(2), 60–68 (2001)CrossRefGoogle Scholar
  14. 14.
    Geem, Z., Sim, K.: Parameter-setting-free harmony Search Algorithm. Applied Mathematics and Computation 217(8), 3881–3889 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  15. 15.
    Ingram, G., Zhang, T.: Overview of Applications and Developments in the Harmony Search Algorithm. In: Geem, Z.W. (ed.) Music-Inspired Harmony Search Algorithm. SCI, vol. 191, pp. 15–37. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  16. 16.
    Kellerer, H., Pferschy, U.: Cardinality Constrained Bin-packing Problems. Annals of Operations Research 92, 335–348 (1999)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Landa-Silva, D., Burke, E.: Asynchronous Cooperative Local Search for the Office-space-allocation Problem. INFORMS Journal on Computing 19(4), 575–587 (2007)MathSciNetzbMATHCrossRefGoogle Scholar
  18. 18.
    Lee, K., Geem, Z.: A New Meta-heuristic Algorithm for Continuous Engineering Optimization: Harmony Search Theory and Practice. Computer Methods in Applied Mechanics and Engineering 194(36-38), 3902–3933 (2005)zbMATHCrossRefGoogle Scholar
  19. 19.
    Ritzman, L., Bradford, J., Jacobs, R.: A Multiple Objective Approach to Space Planning for Academic Facilities. Management Science, 895–906 (1979)Google Scholar
  20. 20.
    Ülker, O., Landa-Silva, D.: A 0/1 integer Programming Model for the Office Space Allocation Problem. Electronic Notes in Discrete Mathematics 36, 575–582 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohammed A. Awadallah
    • 1
  • Ahamad Tajudin Khader
    • 1
  • Mohammed Azmi Al-Betar
    • 1
    • 2
  • Phuah Chea Woon
    • 1
  1. 1.School of Computer SciencesUniversiti Sains Malaysia (USM)Malaysia
  2. 2.Department of Computer ScienceJadara UniversityIrbidJordan

Personalised recommendations