Advanced Approaches to Mathematical Programming: Exact Methods, Metaheuristics, and Machine Learning Synergies
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: 20 May 2025 | Viewed by 88
Special Issue Editors
Interests: operations research; multi-objective optimization algorithms, optimization and decision-making tools
Interests: optimization; metaheuristics; parallel computing; machine learning; computational geometry
Special Issue Information
Dear Colleagues,
Addressing complex real-world optimization challenges necessitates the application of advanced solution methodologies in mathematical programming. This Special Issue, titled "Advanced Approaches to Mathematical Programming: Exact Methods, Metaheuristics, and Machine Learning Synergies", aims to explore diverse methodologies and innovative integrations that move this field forward. By focusing on both individual techniques and their hybridization, this issue seeks to uncover synergies that enhance the efficiency, accuracy, and scalability of solving complex optimization problems.
The scope of this Special Issue includes exact methods, metaheuristics, machine learning techniques, and their combinations, applied to both single and multi-objective optimization problems. Integrating these methodologies opens new avenues in problem-solving by leveraging the strengths of each approach. This synergy is beneficial for addressing complex challenges in fields like logistics, finance, engineering design, and artificial intelligence.
We invite papers that delve into theoretical advancements, practical applications, and innovative integrations of exact methods, metaheuristics, and machine learning in mathematical programming. Contributions highlighting novel algorithms, case studies, comparative analyses, and interdisciplinary research that bridge these approaches are especially welcome.
Dr. Seyed Mahdi Shavarani
Dr. Mahmoud Golabi
Guest Editors
Manuscript Submission Information
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Keywords
- mathematical programming
- machine learning
- operations research
- metaheuristics
- hybrid approaches
- optimization techniques
- multi-objective optimization
- optimization problems
- interdisciplinary applications
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