Optimization of Facility Layout Problems Using Genetic Algorithm
Keywords:
Facility layout problem (FLP), Open-field layout problem (OFLP), Material Handling Cost, Genetic Algorithm, facility layout planning
Abstract
The facility layout problem (FLP) is one of the most important classic industrial engineering and production management problems that have attracted the attention of many researchers over the last few decades. Poor production facility layout planning can result in additional operational costs; one of them is the cost of material handling. Although crucial, FLP is a challenging issue to resolve. A unique method is needed depending on the constraint, case study, and layout type. This research was conducted in order to improve the existing layout of PT. XYZ to minimize material handling costs. The layout type in this case is the Open-field layout problem (OFLP). A genetic algorithm is proposed to optimize the layout. The result is 18.1% material handling costs can be reduced.
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References
Aiello, G., La Scalia, G., & Mario, E. (2013). A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems. Expert Systems with Applications, 40(12), 4812–4819. https://doi.org/10.1016/j.eswa.2013.02.026
Al-Tabtabai, H., & Alex, A. P. (1999). Using genetic algorithms to solve optimization problems in construction. Engineering, Construction and Architectural Management, 6(2), 121–132. https://doi.org/10.1108/eb021105
Datta, D., Amaral, A. R. S., & Figueira, J. R. (2011). Single row facility layout problem using a permutation-based genetic algorithm. European Journal of Operational Research, 213(2), 388–394. https://doi.org/10.1016/j.ejor.2011.03.034
Emami, S., & S. Nookabadi, A. (2013). Managing a new multi-objective model for the dynamic facility layout problem. International Journal of Advanced Manufacturing Technology, 68(9–12), 2215–2228. https://doi.org/10.1007/s00170-013-4820-5
Gonçalves, J. F., & Resende, M. G. C. (2015). A biased random-key genetic algorithm for the unequal area facility layout problem. European Journal of Operational Research, 246(1), 86–107. https://doi.org/10.1016/j.ejor.2015.04.029
Hosseini-Nasab, H., Fereidouni, S., Fatemi Ghomi, S. M. T., & Fakhrzad, M. B. (2018). Classification of facility layout problems: a review study. International Journal of Advanced Manufacturing Technology, 94(1–4), 957–977. https://doi.org/10.1007/s00170-017-0895-8
Izadinia, N., & Eshghi, K. (2016). A robust mathematical model and ACO solution for multi-floor discrete layout problem with uncertain locations and demands. Computers and Industrial Engineering, 96, 237–248. https://doi.org/10.1016/j.cie.2016.02.026
Khaksar-Haghani, F., Kia, R., Mahdavi, I., & Kazemi, M. (2013). A genetic algorithm for solving a multi-floor layout design model of a cellular manufacturing system with alternative process routings and flexible configuration. International Journal of Advanced Manufacturing Technology, 66(5–8), 845–865. https://doi.org/10.1007/s00170-012-4370-2
Kia, R., Khaksar-Haghani, F., Javadian, N., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. Journal of Manufacturing Systems, 33(1), 218–232. https://doi.org/10.1016/j.jmsy.2013.12.005
Kothari, R., & Ghosh, D. (2014). An efficient genetic algorithm for single row facility layout. Optimization Letters, 8(2), 679–690. https://doi.org/10.1007/s11590-012-0605-2
Lenin, N., Siva Kumar, M., Islam, M. N., & Ravindran, D. (2013). Multi-objective optimization in single-row layout design using a genetic algorithm. International Journal of Advanced Manufacturing Technology, 67(5–8), 1777–1790. https://doi.org/10.1007/s00170-012-4608-z
Liu, X. B., & Sun, X. M. (2012). A multi-improved genetic algorithm for facility layout optimisation based on slicing tree. International Journal of Production Research, 50(18), 5173–5180. https://doi.org/10.1080/00207543.2011.654011
Madhusudanan Pillai, V., Hunagund, I. B., & Krishnan, K. K. (2011). Design of robust layout for Dynamic Plant Layout Problems. Computers and Industrial Engineering, 61(3), 813–823. https://doi.org/10.1016/j.cie.2011.05.014
Mohamadghasemi, A., & Hadi-Vencheh, A. (2012). An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns. Computers and Industrial Engineering, 62(1), 342–348. https://doi.org/10.1016/j.cie.2011.10.004
Nasution, A. B. (2015). Implementasi Algoritma Genetika Dalam Optimasi Jalur Pendistribusian Keramik Pada Pt. Chang Jui Fang. Seminar Nasional Informatika 2015, 50–54.
Paes, F. G., Pessoa, A. A., & Vidal, T. (2017). A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem. European Journal of Operational Research, 256(3), 742–756. https://doi.org/10.1016/j.ejor.2016.07.022
Palomo-Romero, J. M., Salas-Morera, L., & GarcÃa-Hernández, L. (2017). An island model genetic algorithm for unequal area facility layout problems. Expert Systems with Applications, 68, 151–162. https://doi.org/10.1016/j.eswa.2016.10.004
Ripon, K. S. N., Glette, K., Khan, K. N., Hovin, M., & Torresen, J. (2013). Adaptive variable neighborhood search for solving multi-objective facility layout problems with unequal area facilities. Swarm and Evolutionary Computation, 8, 1–12. https://doi.org/10.1016/j.swevo.2012.07.003
Said, H., & El-Rayes, K. (2013). Performance of global optimization models for dynamic site layout planning of construction projects. Automation in Construction, 36, 71–78. https://doi.org/10.1016/j.autcon.2013.08.008
Saputro, H. A., Mahmudy, W. F., & Dewi, C. (2015). Implementasi Algoritma Genetika Untuk Optimasi Penggunaan Lahan Pertanian. Jurnal Mahasiswa PTIIK, 5(12), 12.
Umam, M. S., Mustafid, M., & Suryono, S. (2022). A hybrid genetic algorithm and tabu search for minimizing makespan in flow shop scheduling problem. Journal of King Saud University - Computer and Information Sciences, 34(9), 7459–7467. https://doi.org/10.1016/j.jksuci.2021.08.025
Al-Tabtabai, H., & Alex, A. P. (1999). Using genetic algorithms to solve optimization problems in construction. Engineering, Construction and Architectural Management, 6(2), 121–132. https://doi.org/10.1108/eb021105
Datta, D., Amaral, A. R. S., & Figueira, J. R. (2011). Single row facility layout problem using a permutation-based genetic algorithm. European Journal of Operational Research, 213(2), 388–394. https://doi.org/10.1016/j.ejor.2011.03.034
Emami, S., & S. Nookabadi, A. (2013). Managing a new multi-objective model for the dynamic facility layout problem. International Journal of Advanced Manufacturing Technology, 68(9–12), 2215–2228. https://doi.org/10.1007/s00170-013-4820-5
Gonçalves, J. F., & Resende, M. G. C. (2015). A biased random-key genetic algorithm for the unequal area facility layout problem. European Journal of Operational Research, 246(1), 86–107. https://doi.org/10.1016/j.ejor.2015.04.029
Hosseini-Nasab, H., Fereidouni, S., Fatemi Ghomi, S. M. T., & Fakhrzad, M. B. (2018). Classification of facility layout problems: a review study. International Journal of Advanced Manufacturing Technology, 94(1–4), 957–977. https://doi.org/10.1007/s00170-017-0895-8
Izadinia, N., & Eshghi, K. (2016). A robust mathematical model and ACO solution for multi-floor discrete layout problem with uncertain locations and demands. Computers and Industrial Engineering, 96, 237–248. https://doi.org/10.1016/j.cie.2016.02.026
Khaksar-Haghani, F., Kia, R., Mahdavi, I., & Kazemi, M. (2013). A genetic algorithm for solving a multi-floor layout design model of a cellular manufacturing system with alternative process routings and flexible configuration. International Journal of Advanced Manufacturing Technology, 66(5–8), 845–865. https://doi.org/10.1007/s00170-012-4370-2
Kia, R., Khaksar-Haghani, F., Javadian, N., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. Journal of Manufacturing Systems, 33(1), 218–232. https://doi.org/10.1016/j.jmsy.2013.12.005
Kothari, R., & Ghosh, D. (2014). An efficient genetic algorithm for single row facility layout. Optimization Letters, 8(2), 679–690. https://doi.org/10.1007/s11590-012-0605-2
Lenin, N., Siva Kumar, M., Islam, M. N., & Ravindran, D. (2013). Multi-objective optimization in single-row layout design using a genetic algorithm. International Journal of Advanced Manufacturing Technology, 67(5–8), 1777–1790. https://doi.org/10.1007/s00170-012-4608-z
Liu, X. B., & Sun, X. M. (2012). A multi-improved genetic algorithm for facility layout optimisation based on slicing tree. International Journal of Production Research, 50(18), 5173–5180. https://doi.org/10.1080/00207543.2011.654011
Madhusudanan Pillai, V., Hunagund, I. B., & Krishnan, K. K. (2011). Design of robust layout for Dynamic Plant Layout Problems. Computers and Industrial Engineering, 61(3), 813–823. https://doi.org/10.1016/j.cie.2011.05.014
Mohamadghasemi, A., & Hadi-Vencheh, A. (2012). An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns. Computers and Industrial Engineering, 62(1), 342–348. https://doi.org/10.1016/j.cie.2011.10.004
Nasution, A. B. (2015). Implementasi Algoritma Genetika Dalam Optimasi Jalur Pendistribusian Keramik Pada Pt. Chang Jui Fang. Seminar Nasional Informatika 2015, 50–54.
Paes, F. G., Pessoa, A. A., & Vidal, T. (2017). A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem. European Journal of Operational Research, 256(3), 742–756. https://doi.org/10.1016/j.ejor.2016.07.022
Palomo-Romero, J. M., Salas-Morera, L., & GarcÃa-Hernández, L. (2017). An island model genetic algorithm for unequal area facility layout problems. Expert Systems with Applications, 68, 151–162. https://doi.org/10.1016/j.eswa.2016.10.004
Ripon, K. S. N., Glette, K., Khan, K. N., Hovin, M., & Torresen, J. (2013). Adaptive variable neighborhood search for solving multi-objective facility layout problems with unequal area facilities. Swarm and Evolutionary Computation, 8, 1–12. https://doi.org/10.1016/j.swevo.2012.07.003
Said, H., & El-Rayes, K. (2013). Performance of global optimization models for dynamic site layout planning of construction projects. Automation in Construction, 36, 71–78. https://doi.org/10.1016/j.autcon.2013.08.008
Saputro, H. A., Mahmudy, W. F., & Dewi, C. (2015). Implementasi Algoritma Genetika Untuk Optimasi Penggunaan Lahan Pertanian. Jurnal Mahasiswa PTIIK, 5(12), 12.
Umam, M. S., Mustafid, M., & Suryono, S. (2022). A hybrid genetic algorithm and tabu search for minimizing makespan in flow shop scheduling problem. Journal of King Saud University - Computer and Information Sciences, 34(9), 7459–7467. https://doi.org/10.1016/j.jksuci.2021.08.025
Published
2023-10-20
Section
Original Articles
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