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A simultaneous planning of production and scheduling operations in flexible flow shops: case study of tile industry

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Abstract

The aim of this paper is to study a simultaneous lot-sizing and scheduling in multi-product, multi-period flexible flow shop environments. A new mixed integer programming (MIP) model is proposed to formulate the problem. The objective function includes the total cost of production, inventory, and external supply. In this study, in case of not meeting the demand of customers, this demand should be met by foreign suppliers in higher price. Due to the high computational complexity of the studied problem, a rolling horizon heuristic (RHH) and particle swarm optimization algorithm (PSO) are implemented to solve the problem. These algorithms find a feasible and near-optimal from production planning and scheduling. Additionally, Taguchi method is conducted to calibrate the parameters of the PSO algorithm and select the optimal levels of the influential factors. The computational results show that the algorithms are capable of achieving results with good quality in a reasonable time and PSO has better objective values in comparison with RHH. Also, the real case study for tile industry with real features is applied. Sensitivity analysis is used to evaluate the performance of the model.

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References

  1. Almada-Lobo B, James RJW (2010) Neighborhood search meta-heuristics for capacitated lot-sizing with sequence-dependent setups. Int J Prod Res 48(3):861–878

    Article  MATH  Google Scholar 

  2. Almada-Lobo B, Klabjan D, Carravilla MA, Oliveira J (2007) Single machine multiproduct capacitated lotsizing with sequence-dependent setups. Int J Prod Res 45(20):4873–4894

    Article  MATH  Google Scholar 

  3. Bisschop J (2006) AIMMS optimization modeling. Paragon Decision Technology B.V., Harlem

  4. Buschkühl L, Sahling F, Helber S, Tempelmeier H (2010) Dynamic capacitated lot-sizing problems: a classification and review of solution approaches. OR Spectr 32:231–261

    Article  MathSciNet  MATH  Google Scholar 

  5. Chinneck JW (2008) Feasibility and infeasibility in optimization: algorithms and computational methods. Springer Science + Business Media, New York

    MATH  Google Scholar 

  6. Clark A-R, Clark S-J (2000) Rolling-horizon lot-sizing when setup times are sequence-dependent. Int J Prod Res 38(10):2287–2308

    Article  MATH  Google Scholar 

  7. Eberhart R, Kennedy J (1995) A new optimizer using particles swarm Theory, Proc. sixth international symposium on micro machine and human science (Nagoya, Japan). IEEE Service Center, Piscataway, pp 39–43

    Book  Google Scholar 

  8. Fandel G, Stammen-Hegene C (2006) Simultaneous lot sizing and scheduling for multi-product multi-level production. Int J Prod Econ 104(2):308–316

    Article  Google Scholar 

  9. Glover F, Kochenberger G (2005) Handbook of metaheuristics. Kluwer Academic Publishers, Norwell

    MATH  Google Scholar 

  10. Gupta D, Magnusson T (2005) The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times. Comput Oper Res 32:727–747

    Article  MathSciNet  MATH  Google Scholar 

  11. James RJW, Almada-Lobo B (2011) Single and parallel machine capacitated lotsizing and scheduling: new iterative MIP-based neighborhood search heuristics. Comput Oper Res 38(12):1816–1825

    Article  MATH  Google Scholar 

  12. Kennedy J, Eberhart R (1995) Particle swarm optimization, IEEE conference on neural networks, (Perth, Australia), Piscataway, IV, 1942–1948

  13. Kimms A (1996) Multi-level, single-machine lotsizing and scheduling (with initial inventory). Eur J Oper Res 89(1):86–99

    Article  MathSciNet  MATH  Google Scholar 

  14. Kimms A, Drexl A (1998) Some insights into proportional lotsizing and scheduling. J Oper Res Soc 49(11):1196–1205

    Article  MATH  Google Scholar 

  15. Kovacs A, Brown KN, Tarim SA (2009) An efficient MIP model for the capacitated lot-sizing and scheduling problem with sequence-dependent setups. Int J Prod Econ 118:282–291

    Article  Google Scholar 

  16. Menezes AA, Clark A, Almada-Lobo B (2011) Capacitated lot-sizing and scheduling with sequence-dependent, period-overlapping and non-triangular setups. J Sched 14(2):209–219

    Article  MathSciNet  MATH  Google Scholar 

  17. Merece C, Fonton G (2003) MIP-based heuristics for capacitated lotsizing problems. Int J Prod Econ 85(1):97–111

    Article  Google Scholar 

  18. Mohammadi M (2010) Integrating lotsizing, loading and scheduling decisions in flexible flow shops. Int J Adv Manuf Technol 50:1165–1174

    Article  Google Scholar 

  19. Mohammadi M, Fatemi Ghomi SMT, Jafari N (2011) A genetic algorithm for simultaneous lotsizing and sequencing of the permutation flow shops with sequence-dependent setups. Int J Comput Integr Manuf 24(1):87–93

    Article  Google Scholar 

  20. Mohammadi M, Jafari N (2011) A new mathematical model for integrating lot sizing, loading, and scheduling decisions in flexible flow shops. Int J Adv Manuf Technol 55(5):709–721

    Article  Google Scholar 

  21. Mohammadi M, Karimi B, Fatemi Ghomi SMT, Torabi SA (2010) A new algorithmic approach for capacitated lot-sizing problem in flow shops with sequence-dependent setups. Int J Adv Manuf Technol 49:201–211

    Article  MATH  Google Scholar 

  22. Phadke MS (1989) Quality engineering using robust design. Prentice-Hall, USA

    Google Scholar 

  23. Pinedo M (2008) Scheduling: theory, algorithms, and systems, springer, - 3th ed

  24. Ponnambalam SG, Mohan Reddy M (2003) A GA-SA multi objective hybrid search algorithm for integrated lot sizing and sequencing in flow-line scheduling. Int J Adv Manuf Technol 21(2):126–137

    Article  Google Scholar 

  25. Ramezanian R (2013) Integrated lot-sizing and scheduling in capacitated multi-stage production system, Ph.D. Dissertation, Iran

  26. Ramezanian R, Saidi-Mehrabad M, Teymouri E (2013) A mathematical model for integrating lot-sizing and scheduling problem in capacitated flow shop environments. Int J Adv Manuf Technol 66:347–361

    Article  Google Scholar 

  27. Riane F (1998) Scheduling hybrid flowshops: algorithms and applications, PhD thesis, CREGI-FUCaM, Belgium

  28. Shi Y, Eberhart RC (1998) A modified particle swarm optimizer, in proceedings of the IEEE congress on evolutionary computation, 69–73

  29. Urrutia EDG, Aggoune R, Dauzère-Pérès S (2014) Solving the integrated lot-sizing and job-shop scheduling problem. Int J Prod Res 52(17):5236–5254

    Article  Google Scholar 

  30. Wagner HM, Whithin TM (1958) Dynamic version of the economic lot size model. Manag Sci 5:89–96

    Article  MathSciNet  Google Scholar 

  31. Wolosewicz C, Dauzère-Pérès S, Aggoune R (2015) A Lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem. Eur J Oper Res 244(1):3–12

    Article  MathSciNet  MATH  Google Scholar 

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Ramezanian, R., Fallah Sanami, S. & Shafiei Nikabadi, M. A simultaneous planning of production and scheduling operations in flexible flow shops: case study of tile industry. Int J Adv Manuf Technol 88, 2389–2403 (2017). https://doi.org/10.1007/s00170-016-8955-z

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  • DOI: https://doi.org/10.1007/s00170-016-8955-z

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