Location of facilities in the design of the global logistics hub network taking into account the time discount coefficient

Journal of Industrial Engineering International

دوره 18، شماره 4، اسفند 2022، صفحه 1-18   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.30495/jiei.2022.1951379.1202

نویسندگان

Reza Karimi Mehrabadi¹؛ Emad Roghanian^{* 2}؛ shahnaz piroozfar¹؛ Amir Abbas Shojaie¹

¹Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

²دانشکده صنایع دانشگاه خواجه نصیر

چکیده

In this research, the problem of designing a logistics hub network to improve flow management in the implementation of global transport operations has been investigated. In this case, shipments can be moved directly or indirectly between points. In indirect shipping mode, the shipment first enters the hub network and then is sent to customers. In this case, there is a certain discount factor that reduces the time it takes for the product to reach end customers. The objective function of the proposed model is to minimize the fixed costs of constructing a hub, the cost of constructing an inter-hub infrastructure, the cost of transportation if the equipment is transported directly, and the cost of transportation if the hub network is used. The limitations of the model also include locating logistics hubs, managing flow between points, calculating transport time, and finally managing flow between network points. To evaluate the performance of the proposed model, a researcher-made numerical example based on real-world conditions with randomly generated data and sensitivity analysis on the problem outputs was performed. According to the results, it can be seen that the proposed model can produce justified and optimal global answers and therefore can solve real-world problems. Also, based on the sensitivity analysis, it can be seen that with increasing the amount of capacity, the values of the target function decrease. In other words, if capacity is increased, there is a need for fewer vehicles and thus costs are reduced. It is also clear that as capacity increases, the number of vehicles to respond to decreases. In fact, the greater the carrying capacity, the easier it is to manage the flow between the hubs as well as the direct transmission, thus reducing the number of vehicles. In addition, as the cost of building infrastructure increases/decreases, the cost of the entire system is affected.

کلیدواژه‌ها

location؛ global logistics؛ hub network design؛ time discount coefficient

مراجع

[1] Aljuneidi, T., & Bulgak, A. A. (2019). Carbon footprint for designing reverse logistics network with hybrid manufacturing-remanufacturing systems.  Journal of Remanufacturing, 1-20 .

[2] Bhatnagar, R., & Viswanathan, S. (2000). Re-engineering global supply chains: alliances between manufacturing firms and global logistics services providers. International journal of physical distribution & logistics management, 30(1), 13-34 .

[3] Budak, A. (2020). Sustainable reverse logistics optimization with triple bottom line approach: An integration of disassembly line balancing. Journal of Cleaner Production, 122475 .

[4] Cheng, C., Qi, M., Zhang, Y., & Rousseau, L.-M. (2018). A two-stage robust approach for the reliable logistics network design problem. Transportation Research Part B: Methodological, 111, 185-202 .

[5] Darmian, S. M., Moazzeni, S., & Hvattum, L. M. (2020). Multi-objective sustainable location-districting for the collection of municipal solid waste: Two case studies. Computers & Industrial Engineering, 150, 106965.

[6] Dufour, É., Laporte, G., Paquette, J., & Rancourt, M. È. (2018). Logistics service network design for humanitarian response in East Africa. Omega, 74, 1- 14 .

[7] Falcone, E. C., Fugate, B. S., & Dobrzykowski, D. D. (2022). Supply chain plasticity during a global disruption: Effects of CEO and supply chain networks on operational repurposing. Journal of Business Logistics.
[8] Farughi, H., & Mostafayi, S. (2017). A hybrid approach based on ANP, ELECTRE and SIMANP metaheuristic method for outsourcing manufacturing procedures according to supply chain risks-Case study: A medical equipment manufacturer company in Iran. Decision Science Letters, 6(1), 77-94.
[9] Gao, X. (2019). A novel reverse logistics network design considering multi-level investments for facility reconstruction with environmental considerations. Sustainability, 11(9), 2710 .
[10] Guerrero-Lorente, J., Gabor, A. F., & Ponce-Cueto, E. (2020). Omnichannel logistics network design with integrated customer preference for deliveries and returns. Computers & Industrial Engineering, 106433 .
[11] Guerrero, D. (2020). A global analysis of hinterlands from a European perspective. In: Global Logistics Network Modelling and Policy: Quantification and Analysis for International Freight. A global analysis of hinterlands from a European perspective. In: Global Logistics Network Modelling and Policy: Quantification and Analysis for International Freight, 18p .
[12] Jiang, J., Zhang, D., Li, S., & Liu, Y. (2019). Multimodal green logistics network design of urban agglomeration with stochastic demand. Journal of Advanced Transportation, 2019 .
[13] Jiang, J., Zhang, D., Meng, Q., & Liu, Y. (2020). Regional multimodal logistics network design considering demand uncertainty and CO2 emission reduction target: A system-optimization approach. Journal of Cleaner Production, 248, 119304 .
[14] John, S. T., Sridharan, R., & Kumar, P. R. (2018). Reverse logistics network design: a case of mobile phones and digital cameras. The International Journal of Advanced Manufacturing Technology, 94(1), 615-631 .
[15] John, S. T., Sridharan, R., Kumar, P. R., & Krishnamoorthy, M. (2018). Multi-period reverse logistics network design for used refrigerators. Applied Mathematical Modelling, 54, 311-331 .
[16] Kim, Y. G., & Do Chung, B. (2022). Closed-loop supply chain network design considering reshoring drivers. Omega, 102610.
[17] Kuşakcı, A. O ,.Ayvaz, B., Cin, E., & Aydın, N. (2019). Optimization of reverse logistics network of End-of-Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area. Journal of Cleaner Production, 215, 1036-1051 .
[18] Kwag, S. I., & Ko, Y. D. (2019). Optimal design for the Halal food logistics network. Transportation Research Part E: Logistics and Transportation Review, 128, 212-228 .
[19] Lavassani, K. M., Movahedi, B., & Iyengar, R. J. (2022). Multi-layer, multi-tier analysis of global supply chain in medical equipment sector: network science application. Transnational Corporations Review, 1-17.
[20] Li, L., & Liu, Z. P. (2022). A connected network-regularized logistic regression model for feature selection. Applied Intelligence, 1-31.
[21] Liao, T.-Y. (2018). Reverse logistics network design for product recovery and remanufacturing. Applied Mathematical Modelling, 60, 145-163 .
[22] Liu, M., Cao, J., Liang, J., & Chen, M. (2020). Epidemic-Logistics Network Considering Time Windows and Service Level Epidemic-logistics Modeling: A New Perspective on Operations Research (pp. 259-280): Springer.
[23] Lu, S., Zhu, L., Wang ,Y., Xie, L., & Su, H. (2020). Integrated forward and reverse logistics network design for a hybrid assembly-recycling system under uncertain return and waste flows: A fuzzy multi-objective programming. Journal of Cleaner Production, 243, 118591 .
[24] Mangan ,J., & Lalwani, C. L. (2016). Global logistics and supply chain management: John Wiley & Sons .
[25] Mishra, S., & Singh, S. P. (2020). Designing dynamic reverse logistics network for post-sale service. Annals of Operations Research, 1-30 .
[26] Mostafayi, S., Moazeni, S., Dahmardeh, M., & Mokhtari, K. (2015). Vehicle routing problem with regard to simultaneous pickup and delivery, time windows and workers assignment on the basis of their abilities and availability (Vol. 3, No. 1, pp. 423-434). MAGNT Research Report.
[27] Ohmori, S., & Yoshimoto, K. (2019). Global logistics network design problem with rules of origin. Journal of Industrial Engineering and Management, 12(3), 447-457 .
[28] Oyola-Cervantes, J., & Amaya-Mier, R. (2019). Reverse logistics network design for large off-the-road scrap tires from mining sites with a single shredding resource scheduling application. Waste Management, 100, 219-229 .
[29] Park, K., Kim, J., Ko, Y. D., & Song, B. D. (2020). Redesign of reverse logistics network with managerial decisions on the minimum quality level and remanufacturing policy. Journal of the Operational Research Society, 1-14 .
[30] Prinzie, A., & Van den Poel, D. (2005). Constrained optimization of data-mining problems to improve model performance: A direct-marketing application. Expert systems with applications, 29(3), 630-640 .
[31] Rahimi, M., & Ghezavati, V. (2018). Sustainable multi-period reverse logistics network design and planning under uncertainty utilizing conditional value at risk (CVaR) for recycling construction and demolition waste. Journal of Cleaner Production, 172, 1567-1581 .
[32] Reddy, K. N., Kumar, A., & Ballantyne, E. E. (2019). A three-phase heuristic approach for reverse logistics network design incorporating carbon footprint. International Journal of Production Research, 57(19), 6090-6 .114
[33] Robischon, N. (2017). Why Amazon is the world’s most innovative company of 2017. Fast Company .
[34] Sadrnia, A., Langarudi, N. R., & payandeh Sani, A. (2020). Logistics network design to reuse second-hand household appliances for charities. Journal of Cleaner Production, 244, 118717 .

[35] Shah, S., Rutherford, R., & Menon, S. (2020). Emerging technologies of IoT usage in global logistics. Paper presented at the 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM) .
[36] Somnuek, P. (2017). Potential of Tourism Logistic Service Business in the Border Areas of Chong Anma, Chong Sa-Ngam, and Chong Jom Checkpoints in Thailand to Increase Competitive Efficiency among the ASEAN Community. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(4), 844-847 .
[37] Song, D.-W., & Parola, F. (2015). Strategising port logistics management and operations for value creation in global supply chains: Taylor & Francis.

[38] Tohidi, H. (2015). Mathematical modeling of optimal multi fuzzy locations of facilities based on the assumed step distance among them in a convex set. Applied Mathematical Modelling. 39(23–24): 7442-7451, https://doi.org/10.1016/j.apm.2014.12.048.
[39 Tchamyou, V. S. (2017). The role of knowledge economy in African business. Journal of the Knowledge Economy, 8(4), 1189-1228 .
[40] Tosarkani, B. M., Amin, S. H., & Zolfagharinia, H. (2020). A scenario-based robust possibilistic model for a multi-objective electronic reverse logistics network. International Journal of Production Economics, 224, 107557 .
[41] Trochu, J., Chaabane, A., & Ouhimmou, M. (2019). A two-stage stochastic optimization model for reverse logistics network design under dynamic suppliers’ locations. Waste Management, 95, 569-583 .
[42] Trochu, J., Chaabane, A., & Ouhimmou, M. (2020). A carbon-constrained stochastic model for eco-efficient reverse logistics network design under environmental regulations in the crd industry .Journal of Cleaner Production, 245, 118818 .
[43] Vanajakumari, M., Kumar, S., & Gupta, S. (2016). An integrated logistic model for predictable disasters. Production and Operations Management, 25(5), 791-811 .
[44] Vasiliauskas, A. V., & Jakubauskas, G. (2007). Principle and benefits of third party logistics approach when managing logistics supply chain. Transport, 22(2), 68-72 .
[45] Wang, Y., Zhang, S., Guan, X., Peng, S., Wang, H., Liu, Y., & Xu, M. (2020). Collaborative multi-depot logistics network design with time window assignment. Expert Systems with Applications, 140, 112910 .
[46] Wang, Z., Huang, L., & He, C. X. (2019). A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design. Journal of Combinatorial Optimization, 1-28 .
[47] Wang, M., & Huang, H. (2019). The design of a flexible capital-constrained global supply chain by integrating operational and financial strategies. Omega, 88, 40-62.
[48] Yamaguchi, T., Shibasaki, R., Samizo, H., & Ushirooka, H. (2021). Impact on Myanmar’s Logistics Flow of the East–West and Southern Corridor Development of the Greater Mekong Subregion—A Global Logistics Intermodal Network Simulation. Sustainability, 13(2), 668 .
[49] Yan, L., Wen, Y., Teo, K. L., Liu, J., & Xu, F. (2020). Construction of Regional Logistics Weighted Network Model and Its Robust optimization: Evidence from China. Complexity, 2020 .
[50] Yu, H., Sun, X., Solvang, W. D., & Zhao, X. (2 .)020Reverse logistics network design for effective management of medical waste in epidemic outbreaks: Insights from the coronavirus disease 2019 (COVID-19) outbreak in Wuhan (China). International Journal of Environmental Research and Public Health,
17 .1770 ,)5(
[51] Yuchi, Q., Wang, N., Li, S., Yang, Z., & Jiang, B. (2019). A bi-objective reverse logistics network design under the emission trading scheme. IEEE Access, 7, 105072-105085 .
[52] Zarbakhshnia, N., Soleimani, H., Goh, M., & Razavi, S. S. (2019). A novel multi-objective model for green forward and reverse logistics network design. Journal of cleaner production, 208, 1304-1316 .
[53] Zijm, H., Klumpp, M., Heragu, S., & Regattieri, A. (2019). Operations, Logistics and Supply Chain Management: Definitions and Objectives Operations, Logistics and Supply Chain Management (pp. 27-42): Springer