Latest Advances and Applications of Multi-Objective Optimization Techniques
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (10 April 2023) | Viewed by 3042
Special Issue Editors
Interests: multi-objective optimization; social computing
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; artifical intelligent security; complex network; multi-modal data analysis
Special Issues, Collections and Topics in MDPI journals
Interests: evolutionary machine learning; intelligent optimization; data processing and analytics; image and video processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue is devoted to the latest advances and applications of multi-objective optimization techniques in various research areas. As human society develops, various optimization algorithms are designed and widely applied in different areas, such as heuristic algorithms, collaborative game algorithms, multi-time intervals algorithms, etc. Various multi-objective optimization techniques have been developed to prevent falling into local optima and derive desired solutions. When facing conflicting objectives, evolutionary multi-objective optimization techniques efficiently address these complicated scenarios with black-box search/optimization. Furthermore, as artificial intelligence evolves, the optimization of machine learning architectures has become a subject of particular interest. This Special Issue focuses on the latest advances and applications of multi-objective optimization for various real-world theoretical and practical issues. This SI will further contribute to the body of literature on social, mechanical, biomedical, aeronautical, and aerospace engineering, aiming to bring together scholars, researchers, industry personnel, academicians, and individuals in these fields to promote the exchange of novel ideas and findings.
Potential topics include, but are not limited to, the following:
- Multi-agent systems;
- Social computation;
- Data-driven multi-objective computation;
- High-dimensional and many-objective algorithms;
- Evolutionary learning for combinatorial optimization;
- Transport scheduling;
- Automated heuristic design;
- Data-driven multi-objective optimization;
- Parallelized multi-objective optimization;
- Many-objective multi-objective optimization;
- Large-scale multi-objective optimization;
- Machine learning architecture optimization;
- Application of multi-objective optimization bioinformatics, intelligent transportation, smart city, smart sensor networks, cybersecurity, and other critical application areas.
Prof. Dr. Chao Gao
Prof. Dr. Peican Zhu
Prof. Dr. Lianbo Ma
Guest Editors
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