Optimizing inland port scale and function decisions: A bilevel programming approach

Abstract: With the implementation of the Belt and Road Initiative, the inland ports planning is receiving more and more attention. In this work, we aim to determine the scale and function of different potential inland ports in a certain region while considering the cargo flow allocation schemes for the inland ports and seaports in cross-border trade. Unlike previous studies, we consider the dynamic interaction between local government and manufacturing enterprises in the inland port planning process. Based on this, we formulate a bilevel programming model for the considered inland port planning problem, where the upper-level focuses on the local government and the lower-level concentrates on the manufacturing enterprise. To solve the proposed model, we develop a hybrid heuristic algorithm by combining a genetic algorithm and an exact solution method. Furthermore, we conduct a case study of the inland ports planning for the Huaihai Economic Zone in China to verify the applicability of the proposed model and algorithm. The computational results demonstrate that the proposed optimization approach can effectively increase the cross-border transportation market share of inland ports within a limited investment amount and reduce the competition among these inland ports. Our case study also provides valuable management insights on inland port planning in terms of manufacturing enterprises weights, investment limit amount, scale effect, and cargo value weights.

How to cite this paper

 Ma, J., Wang, X., Yang, K., Jiang, L & Gao, Y. (2023). Optimizing inland port scale and function decisions: A bilevel programming approach.International Journal of Industrial Engineering Computations , 14(3), 483-500.

Refrences

Association of Development District in China (2021). China Inland Port Development Report; China Fortune Press: Beijing, BJ. ISBN 9787504775092.
Brouer, B.D., Pisinger, D., & Spoorendonk, S. (2011). Liner Shipping Cargo Allocation with Repositioning of Empty Containers. INFOR: Information Systems and Operational Research, 49(2), pp.109–124. https://doi.org/10.3138/infor.49.2.109.
CFLP (2022). Sixth National Logistics Park (Base) Survey Report. [online] Available at: http://www.chinawuliu.com.cn/lhhzq/202212/16/595027.shtml [Accessed 6 Apr. 2023].
Chagas, G.C., Lorena, L. and Santos R. (2022). A hybrid heuristic for overlapping community detection through the conductance minimization. Physica A: Statistical Mechanics and its Applications, 592, pp.126887–126887. https://doi.org/10.1016/j.physa.2022.126887.
Chang, Z., Yang, D., Wan, Y. and Han, T. (2019). Analysis on the features of Chinese dry ports: Ownership, customs service, rail service and regional competition. Transport Policy, 82(1), pp.107–116. https://doi.org/10.1016/j.tranpol.2018.06.008.
Gasnikov, A.V., Gasnikova, E.V., & Nesterov, Y.E. (2018). Dual Methods for Finding Equilibriums in Mixed Models of Flow Distribution in Large Transportation Networks. Computational Mathematics and Mathematical Physics, 58(9), pp.1395–1403. https://doi.org/10.1134/s0965542518090075.
Ho, M.W., & Ho, K.H. (2006). Risk Management in Large Physical Infrastructure Investments: The Context of Seaport Infrastructure Development and Investment. Maritime Economics & Logistics, 8(2), pp.140–168. https://doi.org/10.1057/palgrave.mel.9100153.
Jiang, L., Wang, X., Yang, K., & Gao, Y. (2022). Bilevel optimization for the reorganization of inland river ports: A niche perspective. Socio-Economic Planning Sciences, 86, p.101466. https://doi.org/10.1016/j.seps.2022.101466.
Kalashnikov, V.V., Dempe, S., Pérez-Valdés, G.A., Kalashnykova, N.I., & Camacho-Vallejo, J.-F. (2015). Bilevel Programming and Applications. Mathematical Problems in Engineering, 2015, pp.1–16. https://doi.org/10.1155/2015/310301.
Kaysi, I., & Nehme, N. (2016). Optimal investment strategy in a container terminal: A game theoretic approach. Maritime Economics & Logistics, 18, 250-26. https://doi.org/10.1057/mel.2015.7.
Koh, Y.-K. (2001). Optimal investment priority in container port development. Maritime Policy & Management, 28(2), pp.109–123. https://doi.org/10.1080/03088830117187.
Lee, H., Song, Y., Choo, S., Chung, K.-Y., & Lee, K.-D. (2013). Bi-level optimization programming for the shipper-carrier network problem. Cluster Computing, 17(3), pp.805–816. https://doi.org/10.1007/s10586-013-0311-6.
Ma, J., Wang, X., Yang, K., & Jiang, L. (2023). Uncertain Programming Model for the Cross-Border Multimodal Container Transport System Based on Inland Ports. Axioms, 12(2), 132. https://doi.org/10.3390/axioms12020132.
Ma, L. (2021). Analysis on the Application of BP Algorithm in the Optimization Model of Logistics Network Flow Distribution. Lecture Notes on Data Engineering and Communications Technologies, 84(1), 67–74. https://doi.org/10.1007/978-981-16-5857-0_9.
Molavi, A., Lim, G. J., & Shi, J. (2020). Stimulating sustainable energy at maritime ports by hybrid economic incentives: A bilevel optimization approach. Applied Energy, 272, 115188. https://doi.org/10.1016/j.apenergy.2020.115188.
National Bureau of Statistics of China (2003). Comparative Analysis of the Development Status of Huaihai Economic Zone. [online] Available at: http://www.stats.gov.cn/ztjc/ztfx/dfxx/200305/t20030512_31192.html.
Qiu, X., & Xu, G. (2019). Optimizing Rail Transport Service in a Dry Port System. IEEE Transactions on Engineering Management, 69(6), 1–15. https://doi.org/10.1109/TEM.2019.2951915.
Qiu, X., Lam, J.S.L., & Huang, G.Q. (2015). A bilevel storage pricing model for outbound containers in a dry port system. Transportation Research Part E: Logistics and Transportation Review, 73, 65–83. https://doi.org/10.1016/j.tre.2014.10.009.
Qu, C., Zeng, Q., Li, K.X., & Lin, K.-C. (2020). Modeling incentive strategies for landside integration in multimodal transport chains. Transportation Research Part A: Policy and Practice, 137, 47–64. https://doi.org/10.1016/j.tra.2020.04.012.
Sinha, A., Malo, P., & Deb, K. (2018). A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications. IEEE Transactions on Evolutionary Computation, 22(2), 276–295. https://doi.org/10.1109/tevc.2017.2712906.
Tao, J., Lu, Y., Ge, D., Dong, P., Gong, X., & Ma, X. (2022). The spatial pattern of agricultural ecosystem services from the production-living-ecology perspective: A case study of the Huaihai Economic Zone, China. Land Use Policy, 122, 106355. https://doi.org/10.1016/j.landusepol.2022.106355.
Vega-Mejía, C., González-Neira, E., Montoya-Torres, J., & Islam, S. (2020). Using a hybrid heuristic to solve the balanced vehicle routing problem with loading constraints. International Journal of Industrial Engineering Computations, 11(2), 255-280.
Vicente, L.N., & Calamai, P.H. (1994). Bilevel and multilevel programming: A bibliography review. Journal of Global Optimization, 5(3), 291–306. https://doi.org/10.1007/bf01096458.
Wang, C., Xie, F., & Xu, L. (2020). Which terminals should expand investment: a perspective of internal non-cooperative competition in a port?. Maritime Policy & Management, 47(6), 718-735. https://doi.org/10.1080/03088839.2020.1725674.
Wang, H., Wang, S., & Meng, Q. (2014). Simultaneous optimization of schedule coordination and cargo allocation for liner container shipping networks. Transportation Research Part E: Logistics and Transportation Review, 70(07), pp.261–273. https://doi.org/10.1016/j.tre.2014.07.005.
Wang, Z., Li, Y., Gu, F., Guo, J., & Wu, X. (2020). Two-sided matching and strategic selection on freight resource sharing platforms. Physica A: Statistical Mechanics and its Applications, [online] 559, p.125014. https://doi.org/10.1016/j.physa.2020.125014.
Yu, P., Wang, Z., Yin, H., Wang, J., & Xu, Z. (2022). Dynamic evolution of shipping network based on hypergraph. Physica A: Statistical Mechanics and its Applications, 598, 127247–127247. https://doi.org/10.1016/j.physa.2022.127247.
Zeng, Q., Maloni, M.J., Paul, J.A., & Zhongzhen Yang, Z. (2013). Dry Port Development in China: Transportation Journal, 52(2), p.234. https://doi.org/10.5325/transportationj.52.2.0234.
Zhang, D., Jiang, J., Li, S., Li, X., & Zhan, Q. (2017). Optimal Investment Timing and Size of a Logistics Park: A Real Options Perspective. Complexity, 2017(1), 1–12. https://doi.org/10.1155/2017/2813816.
Zhang, M., Huang, J., & Zhu, J. (2012). Reliable facility location problem considering facility failure scenarios. Kybernetes, 41(10), pp.1440–1461. https://doi.org/10.1108/03684921211276666.
Zhang, Y., Wu, Y., Wang, W., Yang, Y., & Ma, L. (2021). Novel Multifunctional Dual-Band Coupled-Line Coupler with Reuse of Low-Frequency Trans-Directional and High-Frequency Contra-Directional Functions. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(6), pp.1917–1921. https://doi.org/10.1109/tcsii.2020.3042503.