Intelligent traffic organization for sea ports: Fusing multi-source data for resource allocation and scheduling

Liu, Y, Liu, J, Zhang, Q ORCID: 0000-0002-0651-469X, Liu, Y, Wang, Y and Yang, L (2026) Intelligent traffic organization for sea ports: Fusing multi-source data for resource allocation and scheduling. Ocean Engineering, 354 (2). ISSN 0029-8018

Preview

Text Manuscript_OE_YL.pdf - Accepted Version Available under License Creative Commons Attribution. Download (2MB) | Preview

Abstract

Reliable autonomous traffic organization is critical for smart ports operating under dynamic ocean conditions. This study proposes a comprehensive framework for sea port scheduling based on Multi-Source Information Fusion (MSIF). To address the challenge of fusing heterogeneous data streams-including vessel trajectories, resource availability, and environmental constraints-a Mixed-Integer Programming (MIP) formulation is first established. Subsequently, a high-fidelity digital twin integrating Cellular Automata (CA) and Multi-Agent Systems (MAS) is developed to simulate heterogeneous cooperative behaviours and stochastic uncertainties. Crucially, a novel Simulation-based Multi-Objective Genetic Algorithm (SMOGA) serves as the autonomous decision-making engine, fusing simulation feedback with evolutionary search to optimize vessel sequencing and resource allocation dynamically. Validated with real-world data from Tianjin Port, the framework outperforms both traditional rules and modern swarm intelligence algorithms, increasing throughput by 16.5% and reducing turnaround time by 11.7%. This research demonstrates how fusing multi-scale information into an intelligent evolutionary framework enables robust, autonomous decision-making in congested maritime environments.

Item Type:	Article
Uncontrolled Keywords:	Autonomous systems; Multi-source information fusion; Port traffic management; Simulation-based Multi-Objective Genetic Algorithm (SMOGA); Cooperative autonomy; 4012 Fluid Mechanics and Thermal Engineering; 4005 Civil Engineering; 4015 Maritime Engineering; 40 Engineering; 0405 Oceanography; 0905 Civil Engineering; 0911 Maritime Engineering; Civil Engineering; 4005 Civil engineering; 4012 Fluid mechanics and thermal engineering; 4015 Maritime engineering
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Elsevier
Date of acceptance:	5 March 2026
Date of first compliant Open Access:	10 April 2026
Date Deposited:	09 Apr 2026 13:42
Last Modified:	10 Apr 2026 00:50
DOI or ID number:	10.1016/j.oceaneng.2026.124972
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28354

View Item