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A Comparison of Three Meta-heuristics for a Closed-Loop Layout Problem with Unequal-Sized Facilities

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New Challenges in Applied Intelligence Technologies

Part of the book series: Studies in Computational Intelligence ((SCI,volume 134))

Abstract

This paper presents a novel mathematical model of a closed-loop layout problem with unequal-sized facilities. This problem belongs to a class of combinatorial optimization and NP-hard problems. Obtaining an optimal solution for this complex, large-sized problem in reasonable computational time by using traditional approaches and is extremely difficult. Therefore, we propose three well-known meta-heuristics, namely genetic algorithm (GA), ant colony optimization (ACO), and simulated annealing (SA), to solve the closed-loop layout problem. These algorithms report near-optimal and promising solutions in a short period of time because of their efficiency. The computational results obtained by these algorithms are compared with the results reported by the Lingo 8.0 software package. Finally among our three proposed meta-heuristics, the output of SA is better than other two algorithms and the Lingo.

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References

  1. El-Baz, M.A.: A genetic algorithm for facility layout problems of different manufacturing environments. Computers & Industrial Engineering 47, 233–246 (2004)

    Article  Google Scholar 

  2. Bozer, Y.A., Rim, S.C.: A branch and bound method for solving the bidirectional circular layout problem. Appl. Math. Modeling 20(5), 342–351 (1996)

    Article  MATH  Google Scholar 

  3. Öncan, T., Altınel, İ.K.L.: Exact solution procedures for the balanced unidirectional cyclic layout problem. Eur. J. of Operational Research (to appear, 2007)

    Google Scholar 

  4. Nearchou, A.C.: Meta-heuristics from nature for the loop layout design problem. Int. J. Production Economics 101, 312–328 (2006)

    Article  Google Scholar 

  5. Junjae, C., Peters, B.A.: A simulated annealing algorithm based on a closed loop layout for facility layout design in flexible manufacturing systems. International J. of Prod. Research 44(13), 2561–2572 (2006)

    Article  MATH  Google Scholar 

  6. Bennell, J.A., Potts, C.N., Whitehead, J.D.: Local search algorithms for the min-max loop layout Problem. J. of the Operational Research Society 53, 1109–1117 (2002)

    Article  MATH  Google Scholar 

  7. Goldberg, D.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, New York (1989)

    MATH  Google Scholar 

  8. Kazerooni, M., Luonge, L., Abhary, K.: Cell formation using genetic algorithms. Int. J. of Flexible Automation and Integrated Manufacturing 3(3-4), 283–299 (1995)

    Google Scholar 

  9. Michalewicz, Z.: Genetic algorithms + data structures = evolution programs. Springer, Berlin (1992)

    MATH  Google Scholar 

  10. Tavakkoli-Moghaddam, R., Shayan, E.: Facilities layout design by genetic algorithms. Computers and Industrial Engineering 45(3-4), 527–530 (1998)

    Article  Google Scholar 

  11. Al-Hakim, L.: On solving facility layout problems using genetic algorithms. Int. J. of Production Research 38(11), 2573–2582 (2000)

    Article  MATH  Google Scholar 

  12. Chan, K.C., Tansri, H.: A study of genetic crossover operations on the facility layout problem. Computers and Industrial Engineering 26(3), 537–550 (1994)

    Article  Google Scholar 

  13. Gau, K.Y., Meller, R.D.: An iterative facility layout algorithm. Int. J. of Production Research 37(16), 3739–3758 (1999)

    Article  MATH  Google Scholar 

  14. Hamamoto, S.: Development and validation of genetic algorithm-based facility layout a case study in the pharmaceutical industry. Int. J. of Production Research 37(4), 749–768 (1999)

    Article  MATH  Google Scholar 

  15. Islier, A.A.: A genetic algorithm approach for multiple criteria facility layout design. International Journal of Production Research 36(6), 1549–1569 (1998)

    Article  MATH  Google Scholar 

  16. Levine, J., Ducatelle, F.: Ant colony optimization and local search for bin packing and cutting stock problems. J. of the Operational Research Society 55, 705–716 (2004)

    Article  MATH  Google Scholar 

  17. Gambardella, L.M., Dorigo, M.: An ant colony system hybridized with a new local search for the sequential ordering problem. INFORMS Journal on Computing 12(3), 237–255 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  18. Gambardella, L.M., Taillard, E., Agazzi, G.: MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 63–76. McGraw-Hill, London (1999)

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  20. Wang, T.Y., Wu, K.B., Liu, Y.W.: A simulated annealing algorithm for facility layout problems under variable demand in cellular manufacturing systems. Computers in Industry 46, 181–188 (2001)

    Article  Google Scholar 

  21. Baykasoglu, A., Gindy, N.N.Z.: A simulated annealing algorithm for dynamic layout problem. Computers & Operations Research 28, 1403–1426 (2001)

    Article  MATH  MathSciNet  Google Scholar 

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Ngoc Thanh Nguyen Radoslaw Katarzyniak

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© 2008 Springer-Verlag Berlin Heidelberg

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Panahi, H., Rabbani, M., Tavakkoli-Moghaddam, R. (2008). A Comparison of Three Meta-heuristics for a Closed-Loop Layout Problem with Unequal-Sized Facilities. In: Nguyen, N.T., Katarzyniak, R. (eds) New Challenges in Applied Intelligence Technologies. Studies in Computational Intelligence, vol 134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79355-7_26

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  • DOI: https://doi.org/10.1007/978-3-540-79355-7_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79354-0

  • Online ISBN: 978-3-540-79355-7

  • eBook Packages: EngineeringEngineering (R0)

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