Title: Research on the optimisation of equipment configurations in smart ports based on self-adaptive theory

Authors: Fayi Huang; Dequan Zhou; Yuhan Yang; Xufeng Tang

Addresses: College of Transport and Communications, Shanghai Maritime University, China ' College of Transport and Communications, Shanghai Maritime University, China ' College of Transport and Communications, Shanghai Maritime University, China ' College of Transport and Communications, Shanghai Maritime University, China

Abstract: The importance of international maritime transportation in global trade is self-evident. However, the increasing frequency of maritime trade has imposed greater demands on maritime supply chains. This study aims to investigate the efficient scheduling of multitier equipment in automated container terminals. An integrated model encompassing berths, container yards and transportation subsystems is considered. Owing to the complexity of the proposed model, a comprehensive optimisation framework is developed by combining mathematical optimisation and simulation optimisation methods, along with the application of self-adaptive theory, to achieve optimality for specific indicators in the model. Finally, numerical experiments using real-world data are conducted to verify the effectiveness of the proposed model and algorithm.

Keywords: adaptive genetic algorithm; AGA; simulation optimisation; mixed integer programming; port equipment scheduling.

DOI: 10.1504/IJSTL.2025.149583

International Journal of Shipping and Transport Logistics, 2025 Vol.21 No.4, pp.435 - 466

Received: 04 Jul 2024
Accepted: 02 Apr 2025
Published online: 07 Nov 2025 *

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