Research Article
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The Search for Flexibility in Location and Route Planning: Location Routing Problem Considering Alternative Paths

Year 2025, Volume: 10 Issue: 1, 287 - 315, 28.02.2025
https://doi.org/10.25229/beta.1594825

Abstract

Location Routing Problem (LRP) is an important optimization problem in logistics and supply chain management. This problem aims to reduce costs and increase operational efficiency by combining a number of factors affecting distribution and storage processes. The goal of the study is to propose a flexible modeling approach that minimizes the impact of any disruptions in the distribution network, ensuring that operations are affected as little as possible and deliveries are not disrupted. In this context, the Multi Graph Location Routing Problem (MG-LRP) is considered, which takes into account alternative paths between nodes (warehouses and customers) to optimize warehouse locations and vehicle routes in order to minimize the total cost. A Mixed Integer Linear Programming (MILP) model is proposed for the problem. In order to demonstrate the applicability of the mathematical model, two separate data sets were derived and optimum results were obtained. Furthermore, sensitivity analyses are conducted to examine the impact of considering alternative routes on the solutions. It has been concluded that, although considering alternative routes requires more solution time, it can provide flexibility to the model in obtaining optimal solutions and reduce the total cost.

Ethical Statement

This study, which does not require ethics committee approval and/or legal/special permission, complies with research and publication ethics.

References

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Konum ve Rota Planlamasında Esneklik Arayışı: Alternatif Yolları Dikkate Alan Konum Rotalama Problemi

Year 2025, Volume: 10 Issue: 1, 287 - 315, 28.02.2025
https://doi.org/10.25229/beta.1594825

Abstract

Konum Rotalama Problemi (KRP), lojistik ve tedarik zinciri yönetiminde önemli bir optimizasyon problemidir. Bu problem, dağıtım ve depolama süreçlerini etkileyen bir dizi faktörü birleştirerek, maliyetlerin azaltılması ve operasyonel verimliliğin artırılmasını hedeflemektedir. Çalışmanın amacı, dağıtım ağında meydana gelebilecek herhangi bir aksaklığa karşı operasyonları olabildiğince az etkileyecek ve teslimatları aksatmayacak esnek bir modelleme yaklaşımının önerilmesidir. Bu bağlamda, toplam maliyeti minimize etmek amacıyla depo konumlarını ve araç rotalarını optimize etmeye yönelik, düğümler (depolar ve müşteriler) arasında alternatif yolların hesaba katıldığı, Çoklu Grafikte Konum Rotalama Problemi (ÇG-KRP) ele alınmıştır. Problemin çözümü için Karma Tamsayılı Doğrusal Programlama (KTDP) modeli önerilmiştir. Matematiksel modelin uygulanabilirliğini göstermek amacıyla iki ayrı veri seti türetilmiş ve optimum sonuçlar elde edilmiştir. Ayrıca, dağıtım ağında alternatif yolların dikkate alınmasının çözümler üzerindeki etkisini incelemek amacıyla duyarlılık analizleri gerçekleştirilmiştir. Alternatif yolları dikkate almanın daha fazla çözüm süresi gerektirmesine rağmen optimal çözümler elde edilmesinde modele esneklik kazandırabileceği ve toplam maliyeti azaltabileceği sonucuna varılmıştır.

Ethical Statement

Etik komite onayı ve/veya yasal/özel izin gerektirmeyen bu çalışma, araştırma ve yayın etiğine uygundur.

References

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  • Akpunar, Ö. Ş., & Akpinar, Ş. (2021). A hybrid adaptive large neighbourhood search algorithm for the capacitated location routing problem. Expert Systems with Applications, 168, 114304. https://doi.org/10.1016/j.eswa.2020.114304
  • Albareda-Sambola, M., Fernández, E., & Laporte, G. (2007). Heuristic and lower bound for a stochastic location-routing problem. European Journal of Operational Research, 179(3), 940-955. https://doi.org/10.1016/j.ejor.2005.04.051
  • Alinaghian, M., & Naderipour, M. (2016). A novel comprehensive macroscopic model for time-dependent vehicle routing problem with multi-alternative graph to reduce fuel consumption: A case study. Computers & Industrial Engineering, 99, 210-222. https://doi.org/10.1016/j.cie.2016.07.029
  • Andelmin, J., & Bartolini, E. (2017). An exact algorithm for the green vehicle routing problem. Transportation Science, 51(4), 1288-1303. https://doi.org/10.1287/trsc.2016.0734
  • Andelmin, J., & Bartolini, E. (2019). A multi-start local search heuristic for the green vehicle routing problem based on a multigraph reformulation. Computers & Operations Research, 109, 43-63. https://doi.org/10.1016/j.cor.2019.04.018
  • Androutsopoulos, K. N., & Zografos, K. G. (2017). An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations. Transportation Research Part C: Emerging Technologies, 82, 180-209. https://doi.org/10.1016/j.trc.2017.06.013
  • Araghi, M. E. T., Tavakkoli-Moghaddam, R., Jolai, F., & Molana, S. M. H. (2021). A green multi-facilities open location-routing problem with planar facility locations and uncertain customer. Journal of Cleaner Production, 282, 124343. https://doi.org/10.1016/j.jclepro.2020.124343
  • Baldacci, R., Bodin, L., & Mingozzi, A. (2006). The multiple disposal facilities and multiple inventory locations rollon–rolloff vehicle routing problem. Computers & Operations Research, 33(9), 2667-2702. https://doi.org/10.1016/j.cor.2005.02.023
  • Baldacci, R., Mingozzi, A., & Wolfler Calvo, R. (2011). An exact method for the capacitated location-routing problem. Operations Research, 59(5), 1284-1296. https://doi.org/10.1287/opre.1110.0989
  • Bard, J. F., & Nananukul, N. (2009). Heuristics for a multiperiod inventory routing problem with production decisions. Computers & Industrial Engineering, 57(3), 713-723. https://doi.org/10.1016/j.cie.2009.01.020
  • Behnke, M., & Kirschstein, T. (2017). The impact of path selection on GHG emissions in city logistics. Transportation Research Part E: Logistics and Transportation Review, 106, 320-336. https://doi.org/10.1016/j.tre.2017.08.011
  • Behnke, M., Kirschstein, T., & Bierwirth, C. (2021). A column generation approach for an emission-oriented vehicle routing problem on a multigraph. European Journal of Operational Research, 288(3), 794-809. https://doi.org/10.1016/j.ejor.2020.06.035
  • Belenguer, J. M., Benavent, E., Prins, C., Prodhon, C., & Calvo, R. W. (2011). A branch-and-cut method for the capacitated location-routing problem. Computers & Operations Research, 38(6), 931-941. https://doi.org/10.1016/j.cor.2010.09.019
  • Bozkaya, B., Salman, F. S., & Telciler, K. (2017). An adaptive and diversified vehicle routing approach to reducing the security risk of cash‐in‐transit operations. Networks, 69(3), 256-269. https://doi.org/10.1002/net.21735
  • Breunig, U., Baldacci, R., Hartl, R. F., & Vidal, T. (2019). The electric two-echelon vehicle routing problem. Computers & Operations Research, 103, 198-210. https://doi.org/10.1016/j.cor.2018.11.005
  • Caramia, M., & Guerriero, F. (2009). A heuristic approach to long-haul freight transportation with multiple objective functions. Omega, 37(3), 600-614. https://doi.org/10.1016/j.omega.2008.02.001
  • Drexl, M., & Schneider, M. (2015). A survey of variants and extensions of the location-routing problem. European Journal of Operational Research, 241(2), 283-308. https://doi.org/10.1016/j.ejor.2014.08.030
  • Ehmke, J. F., Campbell, A. M., & Thomas, B. W. (2016). Vehicle routing to minimize time-dependent emissions in urban areas. European Journal of Operational Research, 251(2), 478-494. https://doi.org/10.1016/j.ejor.2015.11.034
  • Ehmke, J. F., Campbell, A. M., & Thomas, B. W. (2018). Optimizing for total costs in vehicle routing in urban areas. Transportation Research Part E: Logistics and Transportation Review, 116, 242-265. https://doi.org/10.1016/j.tre.2018.06.008
  • Escobar-Vargas, D., & Crainic, T. G. (2024). Multi-attribute two-echelon location routing: Formulation and dynamic discretization discovery approach. European Journal of Operational Research, 314(1), 66-78. https://doi.org/10.1016/j.ejor.2023.09.031
  • Fröhlich, G. E., Doerner, K. F., & Gansterer, M. (2020). Secure and efficient routing on nodes, edges, and arcs of simple‐graphs and of multi‐graphs. Networks, 76(4), 431-450. https://doi.org/10.1002/net.21993
  • Gao, S., Wang, Y., Cheng, J., Inazumi, Y., & Tang, Z. (2016). Ant colony optimization with clustering for solving the dynamic location routing problem. Applied Mathematics and Computation, 285, 149-173. https://doi.org/10.1016/j.amc.2016.03.035
  • Garaix, T., Artigues, C., Feillet, D., & Josselin, D. (2010). Vehicle routing problems with alternative paths: An application to on-demand transportation. European Journal of Operational Research, 204(1), 62-75. https://doi.org/10.1016/j.ejor.2009.10.002
  • Heni, H., Renaud, J., & Coelho, L. C. (2018). Time-dependent vehicle routing problem with emission and cost minimization considering dynamic paths. Teknik Rapor. CIRRELT-2018-14. Erişim: 14.05.2024, https://www.cirrelt.ca/documentstravail/cirrelt-2018-14.pdf
  • Hou, D. K., Fan, H. M., Lv, Y. C., & Ren, X. X. (2022). Dynamic multicompartment refrigerated vehicle routing problem with multigraph based on real‐time traffic ınformation. Journal of Advanced Transportation, 2022(1), 5538113. https://doi.org/10.1155/2022/5538113
  • Huang, Y., Zhao, L., Van Woensel, T., & Gross, J. P. (2017). Time-dependent vehicle routing problem with path flexibility. Transportation Research Part B: Methodological, 95, 169-195. https://doi.org/10.1016/j.trb.2016.10.013
  • Karimpour, A., Setak, M., & Hemmati, A. (2023). Estimating energy consumption and charging duration of electric vehicle in multigraph. Computers & Operations Research, 155, 106216. https://doi.org/10.1016/j.cor.2023.106216
  • Lai, D. S., Demirag, O. C., & Leung, J. M. (2016). A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph. Transportation Research Part E: Logistics and Transportation Review, 86, 32-52. https://doi.org/10.1016/j.tre.2015.12.001
  • Laporte, G., Nobert, Y., & Arpin, D. (1986). An exact algorithm for solving a capacitated location-routing problem. Annals of Operations Research, 6, 291-310. https://doi.org/10.1007/BF02023807
  • Li, Y., Lim, M. K., Tseng, M. L., Lin, Y., Shi, Y., Huang, X., & Xiong, W. (2024). A literature review of green location routing problem: a comprehensive analysis of problems, objectives and methodologies. International Journal of Logistics Research and Applications, 1-20. https://doi.org/10.1080/13675567.2024.2332362
  • Liu, X., Qi, M., & Cheng, C. (2017). Green vehicle routing problem with path flexibility. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, ss. 1037-1041. https://doi.org/10.1109/IEEM.2017.8290050
  • Lopes, R. B., Ferreira, C., Santos, B. S., & Barreto, S. (2013). A taxonomical analysis, current methods and objectives on location‐routing problems. International Transactions in Operational Research, 20(6), 795-822. https://doi.org/10.1111/itor.12032
  • Mara, S. T. W., Kuo, R. J., & Asih, A. M. S. (2021). Location‐routing problem: a classification of recent research. International Transactions in Operational Research, 28(6), 2941-2983. https://doi.org/10.1111/itor.12950
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Details

Primary Language Turkish
Subjects Transport Economics, Business Administration
Journal Section Research Articles
Authors

Ergül Kısa Toğrul 0000-0002-7755-5173

Early Pub Date February 27, 2025
Publication Date February 28, 2025
Submission Date December 2, 2024
Acceptance Date January 22, 2025
Published in Issue Year 2025 Volume: 10 Issue: 1

Cite

APA Kısa Toğrul, E. (2025). Konum ve Rota Planlamasında Esneklik Arayışı: Alternatif Yolları Dikkate Alan Konum Rotalama Problemi. Bulletin of Economic Theory and Analysis, 10(1), 287-315. https://doi.org/10.25229/beta.1594825

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