Hyper-heuristic algorithm for hubport hinterland division and transportation network optimization with low-carbon orientation
DOI: https://doi.org/10.3846/transport.2026.27955Abstract
To mitigate resource inefficiencies arising from the homogeneous competition among ports and advance a low-carbon transportation network of hubports, multimodal freight transportation systems with low-pollution and low-consumption have gained significant scholarly attention. In the port hinterland transportation network, a reasonable hinterland for the main hubport can effectively eliminate homogeneous competition, realize the optimal allocation of transport resources, and promote the integrated and coordinated development of the region. From the perspective of hinterland division and coordination of transportation organization methods, a multi-objective mixed integer programming model is established to minimize the total transportation cost, total transportation time, and carbon emission cost. A novel CF-based selection Hyper-Heuristic (HH) is developed that employs an initial population generation mechanism based on tabu-list and an elite solution pool to explore the solution space. A case study of the Yangtze River Delta in China is conducted to verify the validity of the model and algorithm. The results show that the hinterland of Shanghai Port and Ningbo-Zhoushan Port are basically equal in scope, the Shanghai Port is in the upper part of the Yangtze River Delta region, mainly in Jiangsu and parts of Anhui and the Ningbo-Zhoushan Port is in the lower part of the Yangtze River Delta region and Jiangxi. Additionally, the carbon emission reduction effect reaches 34.2%. Finally, this research contributes dual policy implications: network design guidelines for port authorities, and carbon trading mechanism refinements through regional spatialization.
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transportation network, multi-objective mixed integer programming, hyper-heuristic algorithm, carbon emission, hubportHow to Cite
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