Evolutionary Algorithms for Engineering Optimization, Fuzzy Control, and Decision Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".
Deadline for manuscript submissions: 20 January 2027 | Viewed by 550
Special Issue Editors
Interests: signal processing; modeling; prediction, optimization, energy sustainability and control systems for intelligent buildings
Interests: energy consumption; prediction; neural networks models; materials; optimization; fuzzy control; decision systems in intelligent buildings
Interests: robot manipulator; control of electrical machines; control of mechatronic systems; renewable energies
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent control; sparse optimisation; robot control; reinforcement learning; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing complexity of engineering systems, together with the need for accurate decision-making in uncertain environments, has driven the development of evolutionary algorithms and fuzzy techniques as key tools in modern computational intelligence. This Special Issue focuses on recent advances in evolutionary optimization, fuzzy control, and intelligent decision-making systems, encouraging the integration of bio-inspired methods, hybrid approaches, and models capable of operating under uncertainty. Authors are invited to submit theoretical, experimental, and applied contributions that expand the state of the art in these areas and demonstrate their impact on real-world engineering and applied science problems.
The purpose of this Special Issue is to gather recent contributions related to the design, analysis, and application of evolutionary algorithms and metaheuristic techniques in engineering optimization, fuzzy control, and intelligent decision-making systems. Since many theoretical and practical problems involve uncertainty, nonlinearity, and complex constraints, evolutionary and bio-inspired methods have proven to serve as fundamental tools for developing robust, efficient, and adaptive solutions. This Special Issue invites researchers and professionals in engineering, applied mathematics, artificial intelligence, automatic control, and computational sciences to submit original research articles, comparative studies, reviews, and hybrid developments that integrate evolutionary algorithms with fuzzy modeling, advanced optimization, and intelligent decision systems.
Topics of interest include, but are not limited to, the following:
- Evolutionary algorithms applied to engineering optimization.
- Metaheuristics for constrained optimization.
- Bio-inspired algorithms for fuzzy control and intelligent systems.
- Optimization of membership functions and fuzzy rule bases.
- Hybrid methods combining fuzzy logic and evolutionary computation.
- Multi-objective optimization in engineering and fuzzy systems.
- Modeling and decision-making under uncertainty using evolutionary techniques.
- Swarm intelligence applied to control and decision systems.
- Convergence, stability, and robustness analysis of metaheuristics.
- Applications in robotics, energy, transportation, manufacturing, automation, and healthcare.
This Special Issue aims to serve as an interdisciplinary forum connecting evolutionary optimization, fuzzy systems, and modern engineering, promoting new theoretical developments and high-impact applications.
Prof. Dr. José Gabriel Ríos Moreno
Prof. Dr. Mario Trejo-Perea
Prof. Dr. Roberto Valentin Carrillo-Serrano
Prof. Dr. Wanquan Liu
Guest Editors
Manuscript Submission Information
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Keywords
- evolutionary algorithms
- engineering optimization
- fuzzy control
- decision systems
- metaheuristics
- bio-inspired optimization
- swarm intelligence
- multi-objective optimization
- uncertainty modeling
- soft computing
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