IJACSA Special Issue on Learning-based Evolutionary Algorithms and Their Applications

Scope of this Special Issue

This special issue focuses on recent advances in learning-based evolutionary algorithms and their applications in various fields.

• Algorithm design for learning-based evolutionary algorithm
• Multi-objective learning-based evolutionary algorithm
• Hyperparameter optimization of learning-based evolutionary algorithm
• Convergence analysis of learning-based evolutionary algorithm
• Time complexity analysis of learning-based evolutionary algorithm
• Learning mechanism analysis of learning-based evolutionary algorithm
• Bechmark for learning-based evolutionary algorithm
• Learning-based evolutionary algorithm for numerical optimization
• Learning-based evolutionary algorithm for combinatorial optimization
• Other real-world applications

Submission Guidelines:

Authors must follow the journal guidelines available at http://thesai.org/Publications/Guidelines.

Research articles, review articles as well as communications are invited.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a double blind peer-review process.

There is a fixed publication fee of GBP 500 for all accepted manuscripts. Only registered manuscripts will be part of the published special issue.

Authors may submit their manuscripts as per the following schedule:

• Submission Deadline: 31 July 2025
• Review Notification: 30 September 2025
• Registration Deadline: 15 October 2025
• Camera Ready Submission: 31 October 2025
• Final publication: December 2025

Manuscripts should be submitted via email to yanjiesong96@gmail.com. Subject line should be: "IJACSA Special Issue on Learning-based Evolutionary Algorithms and Their Applications".

Guest Editors

Ziyi Chen received his B.S. degree and Ph.D degree in Engineering from National University of Defense Technolgy, Changsha, China, in 2017 and 2023. He is also a joint Ph.D with Combinatorial Optimization and Decision Support group(CODeS), KU Leuven from 2019 to 2021. He has pulished more than 20 papers in Applied Soft Computing, Computers & Industrial Engineering and other journals. He has authored 2 academic book, obtained 10 National Invention Patents, and hosted/participated in more than 10 projects. His research interests include heuristic algorithm, combinatorial optimization, complex system scheduling and deep reinforcement learning. He is now the reviewer of the Knowledge-Based Systems, Frontiers of Engineering Management, Concurrency and Computation: Practice and Experience, Memetic Computing.

Yanjie Song received double B.S. degrees in Management from Tianjin University, Tianjin, China, in 2017 and the Ph.D. degree in Engineering from National University of Defense Technology, Changsha, China, in 2023. He is a Visiting Professor with the National Engineering Research Center of Maritime Navigation System, Dalian Maritime University. He has published more than 50 papers in IEEE Transactions on Evolutionary Computation, IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Systems, Man, and Cybernetics: Systems and other journals. He has authored 4 academic book, obtained 9 National Invention Patents, and hosted/participated in more than 15 projects. His research interests include computational intelligence, evolutionary algorithm, combinatorial optimization, and deep reinforcement learning. He is now the Associate Editor of the International Journal on Interactive Design and Manufacturing, Guest Editor of the Swarm and Evolutionary Computation, Guest Editor of the Computers & Electrical Engineering. He is also the reviewer of the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics and more than 30 other journals.

Junwei Ou received the B.Sc. degree in computer science from the School of Computer and Science Information Engineering, Henan University, Kaifeng, China, in 2015, the M.Sc. degree in computer science from the College of Information Engineering, Xiangtan University, Xiangtan, China, in 2019, and the Ph.D. degree in Control Science and Engineering from the National University of Defense Technology, Changsha, China, in 2023. He is currently a Lecturer with the School of Computer Science and School of Cyberspace Science, Xiangtan University. He has published more than 20 papers in IEEE Transactions on Evolutionary Computation, IEEE Transactions on Aerospace and Electronic Systems, Swarm and Evolutionary Computation, Information Sciences, Applied Soft Computing, Knowledge-Based Systems, Expert Systems With Applications, and other journals. His research interests include evolutionary computation, multiobjective optimization, and resource scheduling.

Wei Hu received his Ph.D. degree in CRIStAL, UMR CNRS 9189, Centrale Lille, France. He is currently an Associate Professor at School of Systems Science, Beijing Jiaotong University, China. His research interests include evolutionary algorithms and their applications, control and sychronization of complex networks, parameter identification of nonlinear systems, nonlinear dynamics and control. He has publish more than 20 papers, including Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, Information Sciences, Nonlinear Dynamics, Communications in Nonlinear Science and Numerical Simulation. He has presided over or participated in the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities, etc. He has won the Best Poster Award on 2024 Intemational Conference on New Irends in Computational Intelligence, Second Prize of 2023 Natural Science Award of Chinese association of Automation, etc.

Qiang Feng received his Ph.D. degree in reliability engineering and systems engineering from Beihang University, Beijing, China, and his B.S. degree in mechanical engineering from the same institution. He is currently the deputy director of the Institute of Reliability Engineering at Beihang University, Beijing, China. He serves as an associate professor and Ph.D. supervisor. His current research interests include smart operation and maintenance for swarm systems and intelligent methods for reliability. Dr. Feng has led over 20 projects supported by various companies and industries. In recent years, he has also participated in more than 20 projects funded by government agencies and national commissions. He has published over 100 papers and contributed to 5 book chapters. Additionally, he has won two first prizes for the Provincial Science and Technology Progress Award, two second prizes, and one third prize.

Jiting Li has received his B.S. degree and Ph.D degree in Engineering from National University of Defense Technolgy, Changsha, China, in 2017 and 2022. His research interests include evolutionary algorithms, social computing and multi-criteria decision-making. The applications of his research include satellite planning and scheduling, human resource planning, personnel selection, etc. He has pulished more than 20 papers in journals and academic conference such as Applied Soft Computing, Mathematics, Journal of Systems Engineering and Electronics, IEEE SMC, etc. He has also authored 2 academic books and hosted/participated in 16 research projects.

Lining Xing received the bachelor’s degrees in economics and in science from Xi’an Jiaotong University, Xi’an, China, in 2002, and the Ph.D. degree in management science from the National University of Defense Technology, Changsha, China, in 2009. He visited the School of Computer, University of Birmingham, Birmingham, U.K., from November 2007 to November 2008. He is a Professor with the School of Electronic Engineering, Xidian University, China. His research interests include intelligent optimization methods and scheduling of resources.