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Special Issue on Investigating the Use of Quantum Technologies in Industrial and Practical Applications Submission Date: 2025-12-31 Quantum computing is seen as the next major advancement in computing, capturing significant interest from the scientific community. These technologies utilize quantum mechanics to develop innovative approaches for efficiently solving a diverse range of problems, including those in machine learning, optimization, and simulation. Leveraging quantum phenomena like superposition and entanglement, quantum information processing and hybrid algorithms (which integrate classical and quantum methods) are anticipated to deliver enhanced speed and accuracy in system modeling and solving complex optimization problems. With the increasing interest in this field, quantum computing has already been successfully applied to various use cases, particularly in addressing industrial challenges.
Moreover, quantum technologies are revolutionizing design, control, and monitoring through new quantum sensors that significantly enhance measurement accuracy. By collecting data at the atomic level, advanced versions of everyday technologies will feature more reliable geolocation and less vulnerable guidance systems, which will be fundamental for many industrial applications.
This special issue aims to promote discussions on the latest discoveries and research achievements, as well as the exchange of innovative ideas in the application of quantum technologies to industry.
Guest editors:
Dr. Eneko Osaba
Tecnalia Research & Innovation Foundation
San Sebastian
20009
Spain
E-mail: eneko.osaba@tecnalia.com
Dr. Esther Villar-Rodriguez
Tecnalia Research & Innovation Foundation
San Sebastian
20009
Spain
E-mail: esther.villar@tecnalia.com
Dr. Izaskun Oregi
Tecnalia Research & Innovation Foundation
San Sebastian
20009
Spain
E-mail: izaskun.oregui@tecnalia.com
Special issue information:
Scope of the Special Issue:
This special issue aims to promote discussions on the latest discoveries and research achievements, as well as the exchange of innovative ideas in the application of quantum technologies to industry.
Topics of interest include, but are not limited to:
Hybrid classical-quantum methods for addressing optimization problems.
Application of Quantum Annealers for solving real-world oriented problems.
Development of quantum-gates based methods (QAOA, VQE…).
Quantum Algorithms and Complexity.
Quantum Machine Learning Approaches.
Latest advances of quantum-inspired computation, especially for optimization, machine learning and deep learning.
Quantum sensing applied to industrial settings.
Quantum simulation for complex industrial problems
Applied to the following fields (not limited):
Transportation and logistics: routing problems, efficient management of vehicle fleets, last-mile logistics, traffic flow optimization...
Efficient management of warehouses: bin packing problems, collision-free robot path planning, optimization of empty container movements…
Optimization of industrial processes: job-shop scheduling problem, multi-car paint shop problem…
Environmentally friendly industrial planning.
Design of industrial facilities: quadratic assignment problem...
Manuscript submission information:
Tentative Schedule:
Submission Open Date: March 02, 2025
Submission Deadline: December 31, 2025
Notification of Acceptance: March 02, 2026
Contributed papers must be submitted via the Engineering Applications of Artificial Intelligence online submission system (Editorial Manager?): Please select the article type “VSI: Quantum Technologies for Practical Applications” when submitting the manuscript online.
Please refer to the Guide for Authors to prepare your manuscript.
For any further information, the authors may contact the Guest Editors.
Learn more about the benefits of publishing in a special issue.
Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field.
Keywords:
(Quantum Optimization) OR (Quantum Annealing) OR (Quantum Gates) OR (Quantum Optimization) OR (Quantum Machine Learning) OR (Quantum Sensing)
