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Bi-criteria Optimization in Integrated Layout Design of Cellular Manufacturing Systems Using a Genetic Algorithm

  • I. Jerin Leno
  • S. Saravana Sankar
  • M. Victor Raj
  • S. G. Ponnambalam
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)

Abstract

Traditionally the design of the physical layout of the manufacturing system and that of the material flow path and material handling system are carried out in isolation. In this work, an attempt was made on the integrated layout design, that is, to concurrently design the physical layout and the material handling system using a Genetic Algorithm-based methodology. The proposed algorithm was employed to simultaneously optimize two contradicting objectives viz., 1. Total material handling cost 2. Distance-weighted cost of closeness rating score. The algorithm was tested on four different benchmark layouts and with different initial problem data sets. It was found that the proposed algorithm is able to produce satisfactory solutions consistently within a reasonable computational limit.

Keywords

Integrated Layout Design Genetic Algorithm Multi-objective optimization 

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References

  1. 1.
    Kim, J.G., Kim, Y.D.: A space partitioning method for facility layout problems with shape constraints. IIE Trans. 30, 947–957 (1998)Google Scholar
  2. 2.
    Tate, D.M., Smith, E.A.: Unequal-area facility by genetic search. IIE Trans. 27, 465–472 (1995)CrossRefGoogle Scholar
  3. 3.
    Rajasekharan, M., Peters, B.A., Yang, T.: A genetic algorithm for facility layout design in flexible manufacturing systems. Int. J. Prod. Res. 36, 95–110 (1998)CrossRefzbMATHGoogle Scholar
  4. 4.
    Deb, S.K., Bhattacharyya, B.: Solution of facility layout problems with pickup/drop-off locations using random search techniques. Int. J. Prod. Res. 43, 4787–4812 (2005)CrossRefGoogle Scholar
  5. 5.
    Hu, G.H., Chen, Y.P., Zhou, Z.D., Fang, H.C.: A genetic algorithm for the inter-cell layout and material handling system design. Int. J. Adv. Manuf. Technol. 34, 1153–1163 (2007)CrossRefGoogle Scholar
  6. 6.
    Aiello, G., Enea, M., Galante, G.: An integrated approach to the facilities and material handling system design. Int. J. Prod. Res. 40, 4007–4017 (2002)CrossRefzbMATHGoogle Scholar
  7. 7.
    Wu, Y., Appleton, E.: The optimization of block layout and aisle structure by a genetic algorithm. Comput. Indust. Eng. 41, 371–387 (2002)CrossRefGoogle Scholar
  8. 8.
    Ho, Y.C., Moodie, C.L.: A hybrid approach for concurrent layout design of cells and their flow paths in a tree configuration. Int. J. Prod. Res. 38, 895–928 (2000)CrossRefzbMATHGoogle Scholar
  9. 9.
    Norman, B.A., Arapoglu, R.A., Smith, A.E.: Integrated facilities design using a contour distance metric. IIE Trans. 33, 337–344 (2001)Google Scholar
  10. 10.
    Murata, H., Fujiyoshi, K., Kajitani, Y.: VLSI module placement based on rectangle-packing by the sequence-pair. IEEE Trans. CAD Integ. Circ. Syst. 15, 1518–1524 (1996)CrossRefGoogle Scholar
  11. 11.
    Tang, X., Wong, D.F., Tian, R.: Fast Evaluation of Sequence Pair in Block Placement by Longest Common Subsequence Computation. In: Design, Automation and Test in Europe, pp. 106–111 (2000)Google Scholar
  12. 12.
    Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to algorithms. McGraw-Hill and MIT Press, New York (1990)zbMATHGoogle Scholar
  13. 13.
    Kochhar, J.S., Foster, B.T., Heragu, S.S.: HOPE: A genetic algorithm for the unequal area facility layout problem. Comput. Oper. Res. 25, 583–594 (1998)CrossRefzbMATHGoogle Scholar
  14. 14.
    Poli, R., Langdon, W.B.: Genetic programming with one-point crossover. In: Second Online World Conference on Soft Computing in Engineering Design and Manufacturing, pp. 23–27. Springer, London (1997)Google Scholar
  15. 15.
    Welgama, P.S., Gibson, P.R.: A construction algorithm for the machine layout problem with fixed pick-up and drop-off points. Int. J. Prod. Res. 11, 2575–2590 (1993)CrossRefGoogle Scholar
  16. 16.
    Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, USA (1989)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • I. Jerin Leno
    • 1
  • S. Saravana Sankar
    • 2
  • M. Victor Raj
    • 3
  • S. G. Ponnambalam
    • 4
  1. 1.Sardar Raja College of EngineeringAlengulamIndia
  2. 2.Kalasalingam UniversityIndia
  3. 3.Dr.Sivanthi Aditanar College of EngineeringTiruchendurIndia
  4. 4.Department of MechatronicsMonash UniversityPetaling JayaMalaysia

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