A Genetic Algorithm for the Double Row Layout Problem

Authors

  • Achmad Pratama Rifai Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada https://orcid.org/0000-0003-4890-8344
  • Setyo Tri Windras Mara Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada
  • Putri Adriani Kusumastuti Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada
  • Rakyan Galuh Wiraningrum Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada

:

https://doi.org/10.9744/jti.22.2.85-92

Keywords:

Facility layout planning, Double row layout problem, Genetic algorithm, Material handling cost

Abstract

The double row layout problem (DRLP) is an NP-hard and has many applications in the industry. The problem concerns on arranging the position of  machines on the two rows so that the material handling cost is minimized. Although several mathematical programming models and local heuristics have been previously proposed, there is still a requirement to develop an approach that can solve the problem efficiently. Here, a genetic algorithm is proposed, which is aimed to solve the DRLP in a reasonable and applicable time. The performances of the proposed method, both its obtained objective values and computational time, are evaluated by comparing it with the existing mathematical programming model. The results demonstrate that the proposed GA can find relatively high-quality solutions in much shorter time than the mathematical programming model, especially in the problem with large number of machines.

Author Biography

Achmad Pratama Rifai, Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada

Achmad Pratama Rifai received his B.Eng. from Gadjah Mada University, and M.Eng. from the University of Malaya. He earned his Ph.D. in integrated design engineering at Keio University. Currently, he is a lecturer in the Department of Mechanical and Industrial Engineering, Gadjah Mada University. His current research interests include optimization, metaheuristics, deep learning, and machine vision for manufacturing and production system.

References

Amaral, A. R., On the exact solution of a facility layout problem. European Journal of Operational Research, 173(2), 2006, pp. 508-518.

Amaral, A. R., An exact approach to the one-dimensional facility layout problem, Operations Research, 56(4), 2008, pp. 1026-1033.

Amaral, A. R., Optimal solutions for the double row layout problem. Optimization Letters, 7(2), 2013, pp. 407-413.

Amaral, A. R., A mixed-integer programming formulation for the double row layout of machines in manufacturing systems, International Journal of Production Research, 57(1), 2019, pp. 34-47.

Amaral, A. R. S., A heuristic approach for the double row layout problem, Annals of Operations Research, 2020, pp. 1-36.

Chung, J., and Tanchoco, J. M. A., The double row layout problem, International Journal of Production Research, 48(3), 2010, pp. 709-727.

Datta, D., Amaral, A. R., and Figueira, J. R., Single row facility layout problem using a permutation-based genetic algorithm, European Journal of Operational Research, 213(2), 2011, pp. 388-394.

Deb, K., Multi-objective optimization using evolutionary algorithms (Vol. 16), John Wiley and Sons, 2001.

Goldberg, D. E. Genetic algorithms in search, Optimization, and Machine Learning, 1989.

Hou, S., Wen, H., Feng, S., Wang, H., and Li, Z., Application of layered coding genetic algorithm in optimization of unequal area production facilities layout, Computational Intelligence and Neuroscience, 2019.

Keller, B., and Buscher, U., Single row layout models, European Journal of Operational Research, 245(3), 2015, pp. 629-644.

Mohamadghasemi, A., and Hadi-Vencheh, A., An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns, Computers and Industrial Engineering, 62(1), 2012, pp. 342-348.

Murray, C. C., Smith, A. E., and Zhang, Z., An efficient local search heuristic for the double row layout problem with asymmetric material flow, International Journal of Production Research, 51(20), 2013, pp. 6129-6139.

Rifai, A. P., Dawal, S. Z. M., Zuhdi, A., Aoyama, H., and Case, K., Reentrant FMS scheduling in loop layout with consideration of multi loading-unloading stations and shortcuts, The International Journal of Advanced Manufacturing Technology, 82(9-12), 2016, pp. 1527-1545.

Secchin, L. D., and Amaral, A. R., An improved mixed-integer programming model for the double row layout of facilities, Optimization Letters, 13(1), 2019, pp. 193-199.

Simmons, D. M., One-dimensional space allocation: an ordering algorithm. Operations Research, 17(5), 1969, pp. 812-826.

Wang, S., Zuo, X., Liu, X., Zhao, X., and Li, J., Solving dynamic double row layout problem via combining simulated annealing and mathematical programming. Applied Soft Computing, 37, 2015, pp. 303-310.

Zuo, X., Murray, C. C., and Smith, A. E., Solving an extended double row layout problem using multiobjective tabu search and linear programming, IEEE Transactions on automation science and engineering, 11(4), 2014, pp. 1122-1132.

Downloads

Published

2020-12-07

How to Cite

[1]
A. P. Rifai, S. T. Windras Mara, P. A. Kusumastuti, and R. G. Wiraningrum, “A Genetic Algorithm for the Double Row Layout Problem”, Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 22, no. 2, pp. 85-92, Dec. 2020.