Abstract
Workspace location decision is considered as a complex problem that requires a detail evaluation and analysis approach. The determination process of a location position should be based on various factors and criteria in order to take into consideration all the requirements of the supply chain that are influencing the efficiency and the general performance of the workspace. The role of the workspace can be viewed differently according to the decision-maker preferences and the nature of business area. In this project, we propose an innovative resolution approach for the single workspace location problem in a polygonal area. Our objective is to locate the facility so as to minimize the total distance between the facility, the customers and the suppliers. Our bi-criteria approach is based on the consideration of the distance and the importance factor of each customer and supplier. We used the A-distance measurement and the aggregation methods to represent the real traveled distance as part of the mathematical modeling of the problem. The aim of the study is to determine the workspace location coordinates that put forward the economic, commercial, and ecological efficiency of the supply chain.
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References
Amar, S. H., & Abouabdellah, A. (2015) Analysis of workshop location with Lagrange interpolation. In The 45th International Conference on Computers & Industrial Engineering. CIE45, Metz-France, 28–30 October 2015. https://doi.org/10.1109/eitech.2017.8255295.
Amar, S. H., & Abouabdellah, A. (2016a). Facility layout planning problem: Effectiveness and reliability evaluation system layout designs. In 2016 International Conference on System Reliability and Science (ICSRS 2016), Paris-France, November 2016. https://doi.org/10.1109/icsrs.2016.7815848.
Amar, S. H., & Abouabdellah, A. (2016b). A combined approach for workspace location selection decision problem: A linguistic-mathematical modeling methodology. International Journal of Applied Engineering Research, 11(5), 3726–3730. ISSN 0973-4562.
Ana, Y., Zenga, B., Zhangb, Y., & Zhaoa, L. (2014). Reliable p-median facility location problem: Two-stage robust models and algorithms. Transportation Research Part B: Methodological, 64, 54–72.
Dantrakula, S., Likasiria, C., & Pongvuthithumb, R. (2014). Applied p-median and p-center algorithms for facility location problems. Expert Systems with Applications, 41(8), 3596–3604. https://doi.org/10.1016/j.eswa.2013.11.046.
Demirel, T., Demirel, N. Ç., Kahraman, C. (2010a). Multi-criteria warehouse location selection using Choquet integral. Expert Systems with Applications, 37(5), 3943–3952. https://doi.org/10.1016/j.eswa.2009.11.022.
Demirel, T., Demirel, N. Ç., Kahraman, C. (2010b). Multi-criteria warehouse location selection using Choquet integral. Expert Systems with Applications, 37, 3943–3952. https://doi.org/10.1016/j.eswa.2009.11.022.
Dogan, I. (2012). Analysis of facility location model using Bayesian networks. Expert Systems with Applications,39, 1092–1104. https://doi.org/10.1016/j.eswa.2011.07.109.
Farahani, R. Z., Hekmatfar, M., Fahimnia, B., & Kazemzadeh, N. (2014). Hierarchical facility location problem: Models, classifications, techniques, and applications. Computers & Industrial Engineering, 68, 104–117. https://doi.org/10.1016/j.cie.2013.12.005.
Letchford, A. N., & Miller, S. J. (2014). An aggressive reduction scheme for the simple plant location problem. European Journal of Operational Research, 234(3), 674–682. https://doi.org/10.1016/j.ejor.2013.10.020.
Matsutomi, T., & Ishii, H. (1998). Minimax location problem with a-distance. Journal of the Operations Research Society of Japan, 41(2), 181–195. https://doi.org/10.15807/jorsj.41.181.
Pisinger, W. D., Rasmussen, A. B., & Sandvik, R. (2007). Solution of large quadratic knapsack problems through aggressive reduction. INFORMS Journal on Computing, 19(2), 280–290. https://doi.org/10.1287/ijoc.1050.0172.
Rahmani, A., & MirHassani, S.A. (2014). A hybrid firefly-genetic algorithm for the capacitated facility location problem. Information Sciences, 283, 70–78. https://doi.org/10.1016/j.ins.2014.06.002.
Widmayer, P., Wu, Y. F., & Wong, C. K. (1987). On some distance problems in fixed orientations. SIAM Journal on Computing,16, 728–746. https://doi.org/10.1137/0216049.
Xu, D.-L., et al. (2012). Prioritization method in the fuzzy analytic network process by fuzzy preferences programming method. World Academy of Science, Engineering and Technology.
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Haddou Amar, S., Abouabdellah, A., El Ouazzani, Y. (2019). A Bi-criteria Distance Reduction Approach for Simple Plant Location Problem. In: El Hani, S., Essaaidi, M. (eds) Recent Advances in Electrical and Information Technologies for Sustainable Development. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-05276-8_12
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DOI: https://doi.org/10.1007/978-3-030-05276-8_12
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