Deep learning-enhanced quantum optimization for integrated job scheduling in container terminals

Truong Ngoc Cuong; Hwan–Seong Kim; Le Ngoc Bao Long; Sam–Sang You; Nguyêñ Duy Tân

doi:10.1016/j.engappai.2025.110431

ScienceGate Book Chapters

JOURNAL ARTICLE

Deep learning-enhanced quantum optimization for integrated job scheduling in container terminals

Truong Ngoc Cuong Hwan–Seong Kim Le Ngoc Bao Long Sam–Sang You Nguyêñ Duy Tân

Year: 2025 Journal: Engineering Applications of Artificial Intelligence Vol: 148 Pages: 110431-110431 Publisher: Elsevier BV

DOI: 10.1016/j.engappai.2025.110431

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Quantum Scheduling (production processes) Container (type theory) Distributed computing Artificial intelligence Mathematical optimization Composite material

Metrics

Cited By

43.38

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Quantum Computing Algorithms and Architecture

Physical Sciences → Computer Science → Artificial Intelligence

Cloud Computing and Resource Management

Physical Sciences → Computer Science → Information Systems

Parallel Computing and Optimization Techniques

Physical Sciences → Computer Science → Hardware and Architecture

Deep learning-enhanced quantum optimization for integrated job scheduling in container terminals

Metrics

Citation History

Topics

Related Documents

Digital Twin Enhanced Reinforcement Learning for Integrated Scheduling in Automated Container Terminals*

Multiple equipment scheduling and routing for container terminals using quantum-inspired deep learning

Heuristic-assisted deep learning for integrated scheduling of multiple equipment in automated container terminals

A Reinforcement Learning Approach for Integrated Scheduling in Automated Container Terminals

Simulation-Optimization Approach for Integrated Scheduling at Wharf Apron in Container Terminals