Submission Deadline: 30 March 2026 View: 443 Submit to Special Issue
Prof. Yao-Hsin Chou
Email: yhchou@ncnu.edu.tw
Affiliation: Department of Computer Science and Information Engineering, National Chi Nan University, Puli, 545, Taiwan
Research Interests: computational intelligence, evolutionary computation, financial technology, circuit synthesis and testing, and quantum information science

Optimization lies at the foundation of financial technology, industrial production, business operations, design automation, and emerging digital ecosystems. Many real-world challenges, such as cost minimization, profit maximization, resource allocation, scheduling, and decision-making, can be formulated as optimization problems. With the rapid development of artificial intelligence (AI), quantum computing, and quantum-inspired algorithms, optimization techniques are being transformed to address the complexity and scale of modern systems across diverse domains.
Traditional methods often encounter difficulties in dealing with high-dimensional, nonlinear, interdependent, or multiobjective problems. In contrast, emerging approaches based on AI, quantum computing, and quantum-inspired heuristics, including quantum annealing and hybrid quantum classical solvers, show strong potential to achieve breakthroughs. These techniques enable more effective exploration of search spaces, support efficient decision-making, and deliver scalable solutions in critical domains such as finance and portfolio optimization, network communication, supply chain management, circuit synthesis, electronic design automation, and manufacturing.
This special issue highlights optimization methodologies and their integration with quantum and quantum-inspired paradigms, with particular emphasis on practical applications. By combining methodological innovation with advanced computational techniques, it aims to strengthen the connection between theoretical progress and real-world impact.
Topics of Interest (including but not limited to):
• Quantum and quantum-inspired algorithms for real-world optimization
• Quantum annealing and its applications in financial optimization
• Portfolio optimization, risk management, and financial engineering with quantum methods
• Quantum circuit synthesis, logic optimization, and electronic design automation
• Hybrid quantum–classical frameworks for large-scale decision-making
• Robust and multiobjective optimization under uncertainty
• Optimization for Artificial Intelligence of Things (AIoT) and smart industrial systems
• Optimization methods for communication networks and cybersecurity
• Visualization and interpretability tools for optimization algorithms
• Applications of quantum optimization in supply chain and industrial systems


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