Multi-Objective Optimization: Methods and Applications
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: 30 April 2027 | Viewed by 42
Special Issue Editor
Interests: multi-objective optimization; many-objective optimization; metaheuristic and evolutionary algorithms; swarm intelligence; machine learning-based optimization; hybrid intelligent optimization methods; Pareto-based decision-making; mathematical programming; large-scale optimization problems; real-world applications in engineering, energy, healthcare, and data science
Special Issue Information
Dear Colleagues,
Multi-objective optimization plays a central role in modern mathematical modeling and decision-making, as many real-world problems involve the simultaneous optimization of conflicting objectives. Over the past decades, significant progress has been made in developing efficient algorithms, theoretical frameworks, and computational strategies to address multi-objective and many-objective optimization problems. This Special Issue aims to present the latest advances in multi-objective optimization, with a particular focus on metaheuristic algorithms, machine learning-enhanced optimization methods, and hybrid intelligent approaches. It seeks to provide a platform for researchers to contribute novel theoretical developments, algorithmic innovations, and practical applications.
Topics of interest include evolutionary and swarm-based algorithms, Pareto optimization techniques, decomposition methods, surrogate-assisted optimization, and learning-based optimization strategies. In addition, applications in engineering design, logistics, energy systems, healthcare, data science, and complex decision-making problems are strongly encouraged. Both original research articles and high-quality review papers are welcome. The goal of this Special Issue is to bridge the gap between theory and applications, and to highlight the role of intelligent optimization techniques in solving complex multi-objective problems in science and engineering.
Prof. Dr. Djaafar Zouache
Guest Editor
Manuscript Submission Information
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Keywords
- multi-objective optimization
- many-objective optimization
- Pareto optimization
- Pareto front approximation
- metaheuristics
- evolutionary algorithms
- multi-objective evolutionary algorithms (MOEAs)
- swarm intelligence
- multi-criteria decision analysis (MCDA)
- real-life optimization problems
- engineering optimization
- energy systems optimization
- logistics and transportation optimization
- healthcare optimization
- data science applications
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