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A solution to the facility layout problem having passages and inner structure walls using particle swarm optimization


This paper proposes a new approach called particle swarm optimization (PSO) to derive better solutions for unequal-area facility layouts that are to have inner walls and passages. PSO is a population based optimization tool, has fitness values to evaluate the population, update the population and search for the optimum with random techniques. A heuristic method is adopted for establishing the relationship between the facilities and passages. A comparative study is performed with the existing algorithm and it shows a better performance for the proposed algorithm. The objective of this study is to minimize material flow between facilities while at the same time satisfying the constraints of areas, aspect ratios of the facilities, and inner structure walls and passages. The proposed algorithm based on the PSO in this study was implemented with C++ language.

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  1. 1.

    Tam K-Y, Li S-G (1991) A hierarchical approach to the facility layout problem. Int J Prod Res 29(1):165–184

  2. 2.

    Lee K-Y, Han S-N, Roh M-I (2003) An improved genetic algorithm for facility layout problems having inner structure walls and passages. Comput Oper Res 30:117–138

  3. 3.

    Islier AA (1998) A genetic algorithm approach for multiple criteria facility design. Int J Prod Res 36(6):1549–1569

  4. 4.

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

  5. 5.

    Heragu SS, Alfa AS (1992) Experimental analysis of simulated annealing based algorithms for the layout problem. Eur J Oper Res 57(2):190–202

  6. 6.

    Chan WM, Chan CY, Ip WH (2002) A heuristic algorithm for machine assignment in cellular layout. Comput Ind Eng 44:49–73

  7. 7.

    Yang T, Kuo C (2003) Decision aiding a hierarchical AHP/DEA methodology for the facilities layout design problem. Eur J Oper Res 147:128–136

  8. 8.

    Mir M, Imam MH (2001) A hybrid optimization approach for layout design of un-equal area facilities. Comput Ind Eng 39:49–63

  9. 9.

    Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc IEEE International Conference on Neural Networks, IV:1942-1948

  10. 10.

    Parsopoulos KE, Vrahatis MN (2001) Particle swarm optimization for imprecise problems.

  11. 11.

    Parsopoulos E, Tasoulis DK, Vrahatis N (2003) Multiobjective optimization using parallel vector evaluated Particle swarm optimization.

  12. 12.

    Tandon V, El-Mounayri H, Kishawy H (2002) NC end milling optimization using evolutionary computation. Int J Mach Tools Manuf 42:595–605

  13. 13.

    Drezner Z (1987) A heuristic procedure for the layout of a large number of facilities. Int J Manage Sci 33(7):907–915

  14. 14.

    Eberhart RC, Shi Y (1998) Comparison between genetic algorithms and particle swarm optimization. Proc 7th ICEC, pp 611–616

  15. 15.

    Hassan M-M-D, Hogg G-L, Smith D-R (1986) SHAPE:A construction algorithm for area placement evaluation. Int J Prod Res 24(5):1283–1295

  16. 16.

    Ho YC, Moodie CL (1998) Machine layout with a linear single-row flowpath in an automated manufacturing system. Int J Manuf Syst 17(1):1–22

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Correspondence to R. Christu Paul.

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Paul, R., Asokan, P. & Prabhakar, V. A solution to the facility layout problem having passages and inner structure walls using particle swarm optimization. Int J Adv Manuf Technol 29, 766–771 (2006).

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  • Facility layout problem
  • Heuristic method
  • Inner structure walls
  • Particle swarm optimization
  • Passage