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Fast local search for single row facility layout

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  • Palubeckis, Gintaras

Abstract

Given n facilities of prescribed lengths and a flow matrix, the single row facility layout problem (SRFLP) is to arrange the facilities along a straight line so as to minimize the total arrangement cost, which is the sum of the products of the flows and center-to-center distances between facilities. We propose interchange and insertion neighborhood exploration (NE) procedures with time complexity O(n2), which is an improvement over O(n3)-time NE procedures from the literature. Numerical results show that, for large SRFLP instances, our insertion-based local search (LS) algorithm is two orders of magnitude faster than the best existing LS techniques. As a case study, we embed this LS algorithm into the variable neighborhood search (VNS) framework. We report computational results for SRFLP instances of size up to 300 facilities. They indicate that our VNS implementation offers markedly better performance than the variant of VNS that uses a recently proposed O(n3)-time insertion-based NE procedure.

Suggested Citation

  • Palubeckis, Gintaras, 2015. "Fast local search for single row facility layout," European Journal of Operational Research, Elsevier, vol. 246(3), pages 800-814.
  • Handle: RePEc:eee:ejores:v:246:y:2015:i:3:p:800-814
    DOI: 10.1016/j.ejor.2015.05.055
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    References listed on IDEAS

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    1. Heragu, Sunderesh S. & Kusiak, Andrew, 1991. "Efficient models for the facility layout problem," European Journal of Operational Research, Elsevier, vol. 53(1), pages 1-13, July.
    2. Datta, Dilip & Amaral, André R.S. & Figueira, José Rui, 2011. "Single row facility layout problem using a permutation-based genetic algorithm," European Journal of Operational Research, Elsevier, vol. 213(2), pages 388-394, September.
    3. Keller, Birgit & Buscher, Udo, 2015. "Single row layout models," European Journal of Operational Research, Elsevier, vol. 245(3), pages 629-644.
    4. Uma Kothari & Diptesh Ghosh, 2012. "A Competitive Genetic Algorithm for Single Row Facility Layout," Working Papers id:4915, eSocialSciences.
    5. Kothari, Ravi & Ghosh, Diptesh, 2013. "Tabu search for the single row facility layout problem using exhaustive 2-opt and insertion neighborhoods," European Journal of Operational Research, Elsevier, vol. 224(1), pages 93-100.
    6. Samarghandi, Hamed & Eshghi, Kourosh, 2010. "An efficient tabu algorithm for the single row facility layout problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 98-105, August.
    7. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    8. Heragu, Sunderesh S. & Alfa, Attahiru Sule, 1992. "Experimental analysis of simulated annealing based algorithms for the layout problem," European Journal of Operational Research, Elsevier, vol. 57(2), pages 190-202, March.
    9. Philipp Hungerländer & Franz Rendl, 2013. "A computational study and survey of methods for the single-row facility layout problem," Computational Optimization and Applications, Springer, vol. 55(1), pages 1-20, May.
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    Cited by:

    1. Ghosh, Diptesh, 2016. "Speeding up neighborhood search for the tool indexing problem," IIMA Working Papers WP2016-09-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Parveen Sharma & Sandeep Singhal, 2016. "Design and evaluation of layout alternatives to enhance the performance of industry," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 741-760, December.

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