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Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem

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  • Guan, Jian
  • Lin, Geng

Abstract

In this paper, a hybrid algorithm based on variable neighborhood search and ant colony optimization is proposed to solve the single row facility layout problem. In the proposed algorithm, three neighborhood structures are utilized to enhance the exploitation ability. Meanwhile, new gain techniques are developed to reduce the mathematical calculations of the objective function values. Furthermore, ant colony optimization as the shaking step is used to avoid being stuck at the local optima. In addition, a novel pheromone updating rule has been proposed based on both the best and worst solutions of the ants. A reverse criterion based on edit distance measure is applied to help ants to converge to the best solution and reduce the solution space. Finally, numerical simulation is carried out based on the benchmark instances, and the comparisons with some existing algorithms demonstrate the effectiveness of the proposed algorithm.

Suggested Citation

  • Guan, Jian & Lin, Geng, 2016. "Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem," European Journal of Operational Research, Elsevier, vol. 248(3), pages 899-909.
  • Handle: RePEc:eee:ejores:v:248:y:2016:i:3:p:899-909
    DOI: 10.1016/j.ejor.2015.08.014
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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. 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.
    3. 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.
    4. 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.
    5. Mladenovic, Nenad & Urosevic, Dragan & Pérez-Brito, Dionisio & García-González, Carlos G., 2010. "Variable neighbourhood search for bandwidth reduction," European Journal of Operational Research, Elsevier, vol. 200(1), pages 14-27, January.
    6. 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.
    7. 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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    1. repec:eee:ejores:v:265:y:2018:i:1:p:26-38 is not listed on IDEAS

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