Skip to main content
SpringerLink
Log in

A bi-objective MIP model for facility layout problem in uncertain environment

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Facility layout problem (FLP) is one of the classical and important problems in real-world problems in the field of industrial engineering where efficiency and effectiveness are very important factors. To have an effective and practical layout, the deterministic assumptions of data should be changed. In this study, it is assumed that we have dynamic and uncertain values for departments’ dimensions. Accordingly, each dimension changes in a predetermined interval. Due to this assumption, two new parameters are introduced which are called length and width deviation coefficients. According to these parameters, a definition for layout in uncertain environment is presented and a mixed integer programming (MIP) model is developed. Moreover, two new objective functions are presented and their lower and upper bounds are calculated with four different approaches. It is worth noting that one of the objective functions is used to minimize the total areas, which is an appropriate criterion to appraise layouts in uncertain conditions. Finally, we solve some benchmarks in the literature to test the proposed model and, based on their results, present a sensitivity analysis.

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

Similar content being viewed by others

References

  1. Francis RL, JA White, F. McGinnis (1992) Facility layout and location: an analytical approach. Prentice-Hall

  2. Tompkins JA (2010) Facilities planning, 4th edn. John Wiley, New York

    Google Scholar 

  3. McKendall ARJ, Hakobyan A (2010) Heuristics for the dynamic facility layout problem with unequal-area departments. Eur J Oper Res 201:171–182

    Article  MATH  Google Scholar 

  4. Suresh G, Sahu S (1983) Multiobjective facility layout using simulated annealing. Int J Prod Econ 32(2):239–254

    Article  Google Scholar 

  5. Bazzara MS, Sherali MD (1980) Benders’ partitioning scheme applied to a new formulation of quadratic assignment problem. Nav Res Logist Q 27(1):29–41

    Article  Google Scholar 

  6. Bukard RE, Bonniger T (1983) A heuristic for quadratic Boolean program with application to quadratic assignment problems. Eur J Oper Res 13:347–386

    Google Scholar 

  7. Kaku BK, Thompson GL (1986) An exact algorithm for the general quadratic. Eur J Oper Res 23(3):382–390

    Article  MathSciNet  Google Scholar 

  8. Kusiak, Heragu S (1987) The facility layout problem. Eur J Oper Res 29:229–251

    Article  MathSciNet  MATH  Google Scholar 

  9. Chwif L, Barretto MRP, Moscato LA (1998) A solution to the facility layout problem using simulated annealing. Comput Ind 36:125–132

    Article  Google Scholar 

  10. Matsuzaki K, Irohara T, Yoshimoto K (1999) Heuristic algorithm to solve the multi-floor layout problem with the consideration of elevator utilization. Comput Ind Eng 36:487–502

    Article  Google Scholar 

  11. Ning X, KC Lam, MCK Lam (2010) A decision-making system for construction site layout planning. Automation in Construction

  12. Wald A (1950) Statistical decision functions which minimize the maximum risk. Ann Math 46(2):265–280

    Article  MathSciNet  Google Scholar 

  13. Mulvey JM, Vanderbei RJ (1995) Robust optimization of large scale systems. Oper Res 43(2):264–281

    Article  MathSciNet  MATH  Google Scholar 

  14. Ben-Tal A, LE Ghaoui, A Nemirovski (2009) Robust optimization. Princeton Series in Applied Mathematics. Princeton Series in Applied Mathematics

  15. Ben-Tal A et al (2004) Adjustable robust solutions of uncertain linear programs. Math Program 99:351–376

    Article  MathSciNet  MATH  Google Scholar 

  16. Ben-Tal A, Nemirovski A (2002) Robust optimization—methodology and applications. Math Program 92:453–480

    Article  MathSciNet  MATH  Google Scholar 

  17. Bertsimas D, Sim M (2006) Tractable approximations to robust conic optimization problems. Math Program 107(1):5–36

    Article  MathSciNet  MATH  Google Scholar 

  18. Bertsimas D, Sim M (2003) Robust discrete optimization and network flows. Math Program 98:49–71

    Article  MathSciNet  MATH  Google Scholar 

  19. Soyster A (1973) Convex programming with set-inclusive constraints and application to inexact linear programming. Oper Res 21(5):1154–1157

    Article  MathSciNet  MATH  Google Scholar 

  20. Shore RH, JA Tompkins (1980) Flexible facilities design. Am Inst Ind Eng Trans: p. 200–205

  21. Kulturel-Konak S, Smith AE, Norman BA (2004) Layout optimization considering production uncertainty and routing flexibility. Int J Prod Res 42(21):4475–4493

    Article  MATH  Google Scholar 

  22. Rosenblatt MJ, Lee HL (1987) A robustness approach to facilities design. Int J Prod Res 25(4):479–486

    Article  Google Scholar 

  23. Kouvelis P, Kurawarwala AA, Gutierrez GJ (1992) Algorithms for robust single and multiple period layout planning for manufacturing systems. Eur J Oper Res 63(2):287–303

    Article  MATH  Google Scholar 

  24. Aiello G, Enea M (2001) Fuzzy approach to the robust facility layout in uncertain production environments. Int J Prod Res 39(18):4089–4101

    Article  MATH  Google Scholar 

  25. Azadivar F, Wang J (2000) Facility layout optimization using simulation and genetic algorithms. Int J Prod Res 38(17):4369–4383

    Article  MATH  Google Scholar 

  26. Cheng R, Gen M, Tozawa T (1996) Genetic search for facility layout design under interflows uncertainty. Jpn J Fuzzy Theory Syst 8(2):267–281

    Google Scholar 

  27. Pillai VM, IB Hunagund, KK Krishnan (2011) Design of robust layout for dynamic plant layout problems. Comput Ind Eng. 61

  28. Neghabi H, Eshghi K, Salmani MH (2014) A new model for robust facility layout problem. Inf Sci 278:498–509

    Article  MathSciNet  Google Scholar 

  29. Izadinia N, Eshghi K, Salmani MH (2014) A robust model for multi-floor layout problem. Comput Ind Eng 78:127–134

    Article  Google Scholar 

  30. Heragu SS, Kusiak A (1991) Efficient models for the facility layout problem. Operations 53(1):1–13

    MATH  Google Scholar 

  31. Olson DL, Swenseth SR (1987) A linear approximation for chance-constrained programming. J Oper Res Soc 38(3):261–267

    Article  MATH  Google Scholar 

  32. Legendre A (1794) Élements de géometrie. Paris: Firmin Didot

  33. Tam KY, Li SG (1991) A hierarchical approach to the facility layout problem. Int J Prod Res 29(1):165–184

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Sharif University of Technology, Tehran, 14588-89694, Iran

    Mohammad Hassan Salmani, Kourosh Eshghi & Hossein Neghabi

Authors
  1. Mohammad Hassan Salmani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kourosh Eshghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hossein Neghabi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Hassan Salmani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Salmani, M.H., Eshghi, K. & Neghabi, H. A bi-objective MIP model for facility layout problem in uncertain environment. Int J Adv Manuf Technol 81, 1563–1575 (2015). https://doi.org/10.1007/s00170-015-7290-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-015-7290-0

Keywords

Search

Navigation