Modeling the robust facility layout problem for unequal space considering health and environmental safety criteria under uncertain parameters

Amin Ghaseminejad; Hamed Kazemipoor; Mohammad Fallah

doi:10.31181/dmame622023607

Authors

Amin Ghaseminejad Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
Hamed Kazemipoor Department of Industrial Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran https://orcid.org/0000-0002-1848-8927
Mohammad Fallah Department of Industrial Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran

DOI:

https://doi.org/10.31181/dmame622023607

Keywords:

Multiple objective programming, robust facility layout problem, meta-heuristics algorithm, fuzzy programming, health and environmental safety

Abstract

This study examines the robust facility layout problem (RFLP) while taking into account unpredictable health and environmental safety standards. This problem's major goal is to arrange the departments in various departments of a hall, allot each department the appropriate amount of space, and identify the kind of amenities and equipment needed for each chosen sector. To accomplish the aforementioned objective, five criteria were taken into account: the total cost of department transfer and selection; access to more facilities and equipment; access to firefighting equipment; access to favorable climatic conditions; and the separation of noisy departments from one another. The fuzzy programming approach is utilized in this research to regulate the uncertainty parameters due to the uncertainty of the transfer cost and transfer time parameters. Additionally, by supplying an appropriate chromosome, the precise Epsilon constraint approach, NSGA II, and MOPSO have been employed to tackle the issue. The computational sizes of larger-sized sample problems solved demonstrate the strong performance of the NSGA II in quickly finding effective solutions.

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References

Ahmadi-Javid, A., & Ardestani-Jaafari, A. (2021). The unequal area facility layout problem with shortest single-loop AGV path: how material handling method matters. International Journal of Production Research, 59, 2352–2374. https://doi.org/10.1080/00207543.2020.1733124

Aiello, G., Enea, M., & Galante, G. (2006). A multi-objective approach to facility layout problem by genetic search algorithm and Electre method. Robotics and Computer-Integrated Manufacturing, 22, 447–455. https://doi.org/10.1016/j.rcim.2005.11.002

Allahyari, M. Z., & Azab, A. (2018). Mathematical modeling and multi-start search simulated annealing for unequal-area facility layout problem. Expert Systems with Applications, 91, 46–62. https://doi.org/10.1016/j.eswa.2017.07.049

Anjos, M. F., & Vieira, M. V. (2017). Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions. European Journal of Operational Research, 261, 1–16.

Anjos, M. F., & Vieira, M. V. C. (2021). Mathematical optimization approach for facility layout on several rows. Optimization Letters, 15, 9–23. https://doi.org/10.1007/s11590-020-01621-z

Arostegui, M. A., Kadipasaoglu, S. N., & Khumawala, B. M. (2006). An empirical comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for facilities location problems. International Journal of Production Economics, 103, 742–754. https://doi.org/10.1016/j.ijpe.2005.08.010

Baykasoglu, A., Dereli, T., & Sabuncu, I. (2006). An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems. Omega, 34, 385–396. https://doi.org/10.1016/j.omega.2004.12.001

Chen, C. W., & Sha, D. Y. (2005). Heuristic approach for solving the multi-objective facility layout problem. International Journal of Production Research, 43, 4493–4507. https://doi.org/10.1080/00207540500056383

Dahlbeck, M. (2021). A mixed-integer linear programming approach for the T-row and the multi-bay facility layout problem. European Journal of Operational Research, 295, 443–462. https://doi.org/10.1016/j.ejor.2021.02.044

El-Rayes, K., & Said, H. (2009). Dynamic Site Layout Planning Using Approximate Dynamic Programming. Journal of Computing in Civil Engineering, 23, 119–127. https://doi.org/10.1061/(asce)0887-3801(2009)23:2(119)

Esmikhani, S., Kazemipoor, H., Sobhani, F. M., & Molana, S. M. H. (2022). Solving fuzzy robust facility layout problem equipped with cranes using MPS algorithm and modified NSGA-II. Expert Systems with Applications, 210, 118402. https://doi.org/10.1016/j.eswa.2022.118402

Garcia-Hernandez, L., Salas-Morera, L., Carmona-Muñoz, C., Abraham, A., & Salcedo-Sanz, S. (2020). A novel multi-objective Interactive Coral Reefs Optimization algorithm for the Unequal Area Facility Layout Problem. Swarm and Evolutionary Computation, 55, 103445. https://doi.org/10.1016/j.swevo.2020.100688

Guan, J., & Lin, G. (2016). Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem. European Journal of Operational Research, 248, 899–909. https://doi.org/10.1016/j.ejor.2015.08.014

Guo, W., Jiang, P., & Yang, M. (2022). Unequal area facility layout problem-solving: a real case study on an air-conditioner production shop floor. International Journal of Production Research, 1-18. https://doi.org/10.1080/00207543.2022.2037778

Kumar, R., Edalatpanah, S. A., & Mohapatra, H. (2020). Note on “Optimal path selection approach for fuzzy reliable shortest path problem.” Journal of Intelligent and Fuzzy Systems, 39, 7653–7656. https://doi.org/10.3233/JIFS-200923

Liu, J., & Liu, J. (2019). Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems. Applied Soft Computing Journal, 74, 167–189. https://doi.org/10.1016/j.asoc.2018.10.012

Liu, S., Zhang, Z., Guan, C., Zhu, L., Zhang, M., & Guo, P. (2021). An improved fireworks algorithm for the constrained single-row facility layout problem. International Journal of Production Research, 59, 2309–2327. https://doi.org/10.1080/00207543.2020.1730465

Mohapatra, H., Mohanta, B. K., Nikoo, M. R., Daneshmand, M., & Gandomi, A. H. (2022). MCDM Based Routing for IoT Enabled Smart Water Distribution Network. IEEE Internet of Things Journal Internet of Things Journal, 10, 4271–4280.

Neghabi, H., & Ghassemi Tari, F. (2016). A new concept of adjacency for concurrent consideration of economic and safety aspects in design of facility layout problems. Journal of Loss Prevention in the Process Industries, 40, 603–614. https://doi.org/10.1016/j.jlp.2016.02.010

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, 25, 742–756. https://doi.org/10.1016/j.ejor.2016.07.022

Pourvaziri, H., Salimpour, S., Akhavan Niaki, S. T., & Azab, A. (2022). Robust facility layout design for flexible manufacturing: a doe-based heuristic. International Journal of Production Research, 60, 5633–5654. https://doi.org/10.1080/00207543.2021.1967500

Samarghandi, H., & Eshghi, K. (2010). An efficient tabu algorithm for the single row facility layout problem. European Journal of Operational Research, 205, 98–105. https://doi.org/10.1016/j.ejor.2009.11.034

Turanoğlu, B., & Akkaya, G. (2018). A new hybrid heuristic algorithm based on bacterial foraging optimization for the dynamic facility layout problem. Expert Systems with Applications, 98, 93–104. https://doi.org/10.1016/j.eswa.2018.01.011

Tavakkoli-Moghaddam, R., Javadian, N., Javadi, B., & Safaei, N. (2007). Design of a facility layout problem in cellular manufacturing systems with stochastic demands. Applied Mathematics and Computation, 184(2), 721–728. https://doi.org/10.1016/j.amc.2006.05.172

Ulutas, B., & Islier, A. A. (2015). Dynamic facility layout problem in footwear industry. Journal of Manufacturing Systems, 36, 55–61. https://doi.org/10.1016/j.jmsy.2015.03.004

Wang, C. L., Senaratne, C., & Rafiq, M. (2015). Success traps, dynamic capabilities and firm performance. British Journal of Management, 26(1), 26–44. https://doi.org/10.1111/1467-8551.12066

Zhang, H., Zhang, K., Chen, Y., & Ma, L. (2022). Multi-objective two-level medical facility location problem and tabu search algorithm. Information Sciences, 608, 734–756. https://doi.org/10.1016/j.ins.2022.06.083