A Model of Port-Hinterland Freight Network by Locating Distribution Centers (Case Study: Iran)

Document Type : Original Article

Authors

1 Assistant Professor, Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran

2 Assistant Professor, Industrial Engineering Department, University of Science and Technology, Tehran, Iran

3 Ph. D. Student‌, University of Science and Technology, Tehran, Iran.

Abstract

Global logistics includes transportation in land and sea side. In land, trains and trucks are used to transport goods. The design of the transportation network and connection between land and sea includes determining the location of distribution centers and their connections with the maritime ports. Determining the optimal location and capacity of distribution centers and type of transportation means for the delivery of goods between sea ports, distribution centers and customer nodes, has a high importance in the distribution network's efficiency. In this research, a two-objective math programming model is proposed for locating distribution centers in which multimodal transport is used to connect the port and hinterland. In this model, the internal and external supply and demand flows of each node are intended to determine the location of distribution centers or terminals in hinterland, with the aim of minimizing the transport costs as and pollution caused by vehicles. In this study, the modified Epsilon method has been used to solve the problem. The results of the research showed that the construction of distribution centers and the development of transportation modes should be in the range of 96 to 106 billion dollars. Also, the amount of carbon dioxide produced in each of these investments will be about 40 to 56 million tons a year.

Keywords

References

Chang, Z., Notteboom, T., & Lu, J., (2015), "A two-phase model for dry port location with an application to the port of Dalian in China". Transportation Planning and Technology, 38(4), pp.442–464.
-Crainic, T. G., Dell’Olmo, P., Ricciardi, N., & Sgalambro, A., (2015), "Modeling dry-port-based freight distribution planning". Transportation Research Part C: Emerging Technologies, 55, pp.518–534.
-Cullinane, K., Ping, J., & Wang, T.-F., (2002), "A multi-objective programming approach to the optimisation of china’s international container transport networks". International Journal of Transport Economics/Rivista Internazionale Di Economia Dei Trasporti, pp.181–199.
-Feng, X., Zhang, Y., Li, Y., & Wang, W., (2013), "A location-allocation model for seaport-dry port system optimization". Discrete Dynamics in Nature and Society.
-Halim, R. A., Kwakkel, J. H., & Tavasszy, L. A., (2016), "A strategic model of port-hinterland freight distribution networks". Transportation Research Part E: Logistics and Transportation Review, 95, pp.368–384.
-Iannone, F., (2012), "The private and social cost efficiency of port hinterland container distribution through a regional logistics system. Transportation Research Part A: Policy and Practice, 46(9), pp.1424–1448.
-Iannone, F., & Thore, S., (2010), "An economic logistics model for the multimodal inland distribution of maritime containers". International Journal of Transport Economics/Rivista Internazionale Di Economia Dei Trasporti, pp.281–326.
-Kim, N., Janic, M., & Van Wee, B., (2009), "Trade-off between carbon dioxide emissions and logistics costs based on multiobjective optimization". Transportation Research Record: Journal of the Transportation Research Board, (2139), pp.107–116.
-Lam, J. S. L., & Gu, Y., (2016), "A market-oriented approach for intermodal network optimisation meeting cost, time and environmental requirements". International Journal of Production Economics, 171, pp.266–274.
-Lättilä, L., Henttu, V., & Hilmola, O.-P., (2013), "Hinterland operations of sea ports do matter: Dry port usage effects on transportation costs and CO2 emissions". Transportation Research Part E: Logistics and Transportation Review, 55, pp.23–42.
-Lee, P. T., Hu, K., & Chen, T., (2010), "External costs of domestic container transportation: Short‐sea shipping versus trucking in Taiwan". Transport Reviews, 30(3), pp.315–335.
-Mavrotas, G., (2009), "Effective implementation of the ε-constraint method in multi-objective mathematical programming problems". Applied Mathematics and Computation, 213(2), pp.455–465.
-Mingjun, J. I., & Maoying, H. E., (2010), "Optimization of two-stage port logistics network of dynamic hinterland based on bi-level programming model". Journal of Transportation Systems Engineering and Information Technology, 10(6), pp.89–94.
-Rahimi, M., Asef-Vaziri, A., & Harrison, R., (2008), "An inland port location-allocation model for a regional intermodal goods movement system". Maritime Economics & Logistics, 10(4), 362–379.
-Steuer, R. E., (1986), "Multiple criteria optimization, Theory, Computation and Applications".
-Wang, C., (2008), "Optimization of hub-and-spoke two-stage logistics network in regional port cluster. Systems Engineering-Theory & Practice, 28(9), pp.152–158.
-Wei, H., & Sheng, Z., (2017), "Dry Ports-Seaports Sustainable Logistics Network Optimization: Considering the Environment Constraints and the Concession Cooperation Relationships". Polish Maritime Research, 24(s3), pp.143–151.
-Zhang, M., Janic, M., & Tavasszy, L. A., (2015), "A freight transport optimization model for integrated network, service, and policy design". Logistics and Transportation Review, 77, pp.61–76.
Journal of Transportation Research
Volume 16, Issue 3 - Serial Number 60
October 2019
Pages 111-125

Files

Share

How to cite

Statistics