Optimization Algorithms and Engineering: Recent Advances and Applications
1Southern Illinois University Carbondale, Illinois, USA
2Universidade de Lisboa, Lisbon, Portugal
3Urmia University of Technology, Urmia, Iran
Optimization Algorithms and Engineering: Recent Advances and Applications
Description
In recent years with the development of computer processing capabilities, there has been an opportunity to study engineering issues more accurately, in more detail, taking into account various uncertainties and constraints. By considering various constraints and increasing the number of variables in different engineering problems, the need for more powerful problem-solving methods becomes even more necessary. Evolutionary optimization algorithms are powerful tools for modern engineers and researchers proven by countless implementations.
Optimization techniques could be utilized if an engineering problem can be parameterized, precisely defined, and algorithmically described. Solving real-world problems very often requires connecting several disciplines within the optimization procedure. The progress in the research of evolutionary optimization algorithms continuously pushes the boundary of application feasibility, making the optimization processes more accurate and efficient. Optimization is a higher-level tool, which can play a decisive and positive role in any engineering problem.
This Special Issue aims to collate research applying optimization algorithms in engineering issues, assessing their strengths and weaknesses, applying the necessary adjustment to existing algorithms, and introducing new nature-inspired algorithms. We welcome original research and review articles that implement evolutionary optimization algorithms in engineering problems.
Potential topics include but are not limited to the following:
- Multi-objective engineering problems
- Metaheuristic optimization algorithms and applications
- Graph theory and optimization
- IoT and optimization
- Designing electrical circuits and devices using optimization algorithms
- Signal processing and optimization
- Image processing and optimization
- Neural network and optimization algorithms
- Applications of optimization methods in robotics
- Systems modeling and optimization
- Data science and optimization
- Machine learning and optimization
- Optimization-based artificial intelligence
- Practical applications of optimization techniques in various engineering problems