Skip to main content
SpringerLink
Log in

Mathematical formulation and hybrid meta-heuristic solution approaches for dynamic single row facility layout problem

  • Original Research
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

In this study, for the first time, the classical single row facility layout problem is extended to its dynamic type by considering several planning periods. This new problem consists of two types of costs e.g. material handling cost and rearrangement cost of the departments at the beginning of each period. The problem is formulated by a mixed integer linear programming model. Because of the high complexity of the problem, two well-known meta-heuristic algorithms e.g. the GA and the SA are proposed to solve the problem. In addition, both of the algorithms are hybridized considering the restart and acceptance probability strategies. In order to study the performance of the proposed algorithms, 20 benchmark problems are generated randomly. Considering one of the generated benchmarks, the parameters of the algorithms are tuned by a typical method and final experiments are performed accordingly. The obtained results strongly prove the superiority of the SA hybridized by the restart strategy as it shows much better performance comparing to other proposed algorithms in more than 60% of the benchmarks.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Amaral, A. R. S., & Letchford, A. N. (2013). A polyhedral approach to the single row facility layout problem. Mathematical Programming, 141(1–2), 453–477.

    Google Scholar 

  • Anjos, M. F., & Vannelli, A. (2008). Computing globally optimal solutions for single-row layout problems using semidefinite programming and cutting planes. INFORMS Journal on Computing, 20(4), 611–617.

    Google Scholar 

  • Beghin-Picavet, M., & Hansen, P. (1982). Deux probl‘emes daffectation non lineaires. Recherche Operationnelle, 16(3), 263–276.

    Google Scholar 

  • Boros, P., Fehér, O., Lakner, Z., Niroomand, S., & Vizvári, B. (2016). Modeling supermarket re-layout from the owner’s perspective. Annals of Operations Research, 238(1–2), 27–40.

    Google Scholar 

  • Braglia, M. (1997). Heuristics for single-row layout problems in flexible manufacturing systems. Production Planning & Control, 8(1), 558–567.

    Google Scholar 

  • Datta, D., Amaral, A. R., & Figueira, J. R. (2011). Single row facility layout problem using a permutation-based genetic algorithm. European Journal of Operational Research, 213(2), 388–394.

    Google Scholar 

  • De Jong, K. A. (1975). An Analysis of the behavior of a class of genetic adaptive systems. Doctoral dissertation, University of Michigan, 36(10), 5140B (University Microfilms No. 76-9381).

  • Djellab, H., & Gourgand, M. (2001). A new heuristic procedure for the single-row facility layout problem. International Journal of Computer Integrated Manufacturing, 14(3), 270–280.

    Google Scholar 

  • Ficko, M., Brezocnik, M., & Balic, J. (2004). Designing the layout of single- and multiplerows flexible manufacturing system by genetic algorithms. Journal of Materials Processing Technology, 157–158(1), 150–158.

    Google Scholar 

  • Heragu, S. S., & Alfa, A. S. (1992). Experimental analysis of simulated annealing based algorithms for the facility layout problem. European Journal of Operational Research, 57(1), 190–202.

    Google Scholar 

  • Heragu, S. S., & Kusiak, A. (1988). Machine layout problem in flexible manufacturing systems. Operations Research, 36(2), 258–268.

    Google Scholar 

  • Heragu, S. S., & Kusiak, A. (1991). Efficient models for the facility layout problem. European Journal of Operational Research, 53(1), 1–13.

    Google Scholar 

  • Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. Oxford: U Michigan Press.

    Google Scholar 

  • Hungerlander, P., & Rendl, F. (2013). Semidefinite relaxations of ordering problems. Mathematical Programming B, 140(1), 77–97.

    Google Scholar 

  • Keller, B., & Buscher, U. (2012). Single row layout models. European Journal of Operational Research, 245(3), 629–644.

    Google Scholar 

  • Kirkpatrick, S., Gelatt, C. D., Jr., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220, 671–680.

    Google Scholar 

  • Kothari, R., & Ghosh, D. (2012). The single row facility layout problem: State of the art. OPSEARCH, 49(4), 442–462.

    Google Scholar 

  • Kothari, R., & Ghosh, D. (2013). Insertion based LinKernighan heuristic for single row facility layout. Computers & Operations Research, 40(1), 129–136.

    Google Scholar 

  • Kothari, R., & Ghosh, D. (2014). An efficient genetic algorithm for single row facility layout. Optimization Letters, 6(2), 679–690.

    Google Scholar 

  • Kouvelis, P., & Chiang, W.-C. (1992). A simulated annealing procedure for single row layout problems in flexible manufacturing systems. International Journal of Production Research, 30(4), 717–732.

    Google Scholar 

  • Kouvelis, P., & Chiang, W.-C. (1996). Optimal and heuristic procedures for row layout problems in automated manufacturing systems. Journal of the Operational Research Society, 47(1), 803–816.

    Google Scholar 

  • Kumar, K. R., Hadjinicola, G. C., & Lin, T. L. (1995). A heuristic procedure for the single row facility layout problem. European Journal of Operational Research, 87(1), 65–73.

    Google Scholar 

  • Larranaga, P., Kuijpers, C. M. H., Murga, R. H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13, 129–170.

    Google Scholar 

  • Love, R. F., & Wong, J. Y. (1976). On solving a one-dimensional space allocation problem with integer programming. INFOR, 14(2), 139–144.

    Google Scholar 

  • Niroomand, S., Hadi-Vencheh, A., Şahin, R., & Vizvári, B. (2015a). Modified migrating birds optimization algorithm for closed loop layout with exact distances in flexible manufacturing systems. Expert Systems with Applications, 42(19), 6586–6597.

    Google Scholar 

  • Niroomand, S., Mirzaei, N., Şahin, R., & Vizvári, B. (2015b). A new exact formulation and simulated annealing algorithm for one-sided closed loop layout. Journal of Computational and Theoretical Nanoscience, 12(10), 3817–3826.

    Google Scholar 

  • Niroomand, S., & Vizvári, B. (2013). A mixed integer linear programming formulation of closed loop layout with exact distances. Journal of Industrial and Production Engineering, 30(3), 190–201.

    Google Scholar 

  • Niroomand, S., Takács, S., & Vizvári, B. (2011). To lay out or not to lay out? Annals of Operations Research, 191(1), 183–192.

    Google Scholar 

  • Niroomand, S., & Vizvari, B. (2015). Exact mathematical formulations and metaheuristic algorithms for production cost minimization: A case study of the cable industry. International Transactions in Operational Research, 22(3), 519–544.

    Google Scholar 

  • Ozcelik, F. (2012). A hybrid genetic algorithm for the single row layout problem. International Journal of Production Research, 50(1), 1–15.

    Google Scholar 

  • Palubeckis, G. (2012). A branch-and-bound algorithm for the single-row equidistant facility layout problem. OR Spectrum, 34(1), 1–21.

    Google Scholar 

  • Pasandideh, S. H. R., Akhavan Niaki, S. T., & Asadi, K. (2015). Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Sciences, 292, 57–74.

    Google Scholar 

  • Picard, J. C., & Queyranne, M. (1981). On the one-dimensional space allocation problem. Operations Research, 29(2), 371–391.

    Google Scholar 

  • Ponnambalam, S. G., & Ramkumar, V. (2001). A genetic algorithm for the design of a single-row layout in automated manufacturing systems. The International Journal of Advanced Manufacturing Technology, 58(18), 512–519.

    Google Scholar 

  • Sahin, R., Turkbey, O., & Ertogral, K. (2010). A new hybrid tabu-simulated annealing heuristic for the dynamic facility layout problem. International Journal of Production Research, 47(24), 6855–6873.

    Google Scholar 

  • Samarghandi, H., & Eshghi, K. (2010). An efficient tabu algorithm for the single row facility layout problem. European Journal of Operational Research, 205(1), 98–105.

    Google Scholar 

  • Samarghandi, H., Taabayan, P., & Jahantigh, F. F. (2010). A particle swarm optimization for the single row facility layout problem. Computers & Industrial Engineering, 58(4), 529–534.

    Google Scholar 

  • Simmons, D. M. (1969). One-dimensional space allocation: An ordering algorithm. Operations Research, 17(5), 812–826.

    Google Scholar 

  • Solimanpur, M., Vrat, P., & Shankar, R. (2005). An ant algorithm for the single row layout problem in flexible manufacturing systems. Computers & Operations Research, 32(3), 583–598.

    Google Scholar 

  • Taassori, M., Niroomand, S., Uysal, S., Hadi-Vencheh, A., & Vizvari, B. (2016). Fuzzy-based mapping algorithms to design networks-on-chip. Journal of Intelligent & Fuzzy Systems, 31(1), 27–43.

    Google Scholar 

  • Taassori, M., Niroomand, S., Uysal, S., Vizvari, B., & Hadi-Vencheh, A. (2018). Optimization approaches for core mapping on networks on chip. IETE Journal of Research, 64(3), 394–405.

    Google Scholar 

  • Taassori, M., Taassori, M., Niroomand, S., Vizvari, B., Uysal, S., & Hadi-Vencheh, A. (2015). OPAIC: An optimization technique to improve energy consumption and performance in application specific network on chips. Measurement, 74, 208–220.

    Google Scholar 

  • Teo, Y., & Ponnambalam, S. (2008). A hybrid ACO/PSO heuristic to solve single row layout problem. In 4th IEEE conference on automation science and engineering (pp. 597–602) Washington DC.

  • Tompkins, J. A., White, J. A., Bozer, Y. A., & Tanchoco, J. M. A. (2003). Facilities planning (3rd ed.). New York: Wiley.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey

    Ramazan Şahin & Esra Duygu Durmaz

  2. Department of Industrial Engineering, Firouzabad Institute of Higher Education, Firouzabad, Fars, Iran

    Sadegh Niroomand

  3. Department of Industrial Engineering, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman, Iran

    Saber Molla-Alizadeh-Zavardehi

Authors
  1. Ramazan Şahin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sadegh Niroomand
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Esra Duygu Durmaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saber Molla-Alizadeh-Zavardehi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sadegh Niroomand.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Şahin, R., Niroomand, S., Durmaz, E.D. et al. Mathematical formulation and hybrid meta-heuristic solution approaches for dynamic single row facility layout problem. Ann Oper Res 295, 313–336 (2020). https://doi.org/10.1007/s10479-020-03704-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-020-03704-7

Keywords

Search

Navigation