Engineering Applications of Optimization Algorithms: Heuristics, Metaheuristics, and Hyperheuristics
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 134
Special Issue Editors
Interests: artificial intelligence; optimization algorithms; biomedical engineering; remote healthcare monitoring; prognosis and diagnosis; machine learning; deep learning; swarm and evolutionary algorithms; hyper-heuristic algorithms; biomedical image processing; biomedical signal processing; time-series analysis; internet-of-things; wireless body sensor networks
Special Issues, Collections and Topics in MDPI journals
Interests: optimization; healthcare systems; metaheuristics; machine learning; engineering problems
Interests: scheduling; development of exact and approximate algorithms; stability investigations; discrete optimization; scheduling with interval processing times; complex investigations for scheduling problems; train scheduling; graph theory; logistics; supply chains; packing; simulation; applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Optimization algorithms are powerful tools for solving a wide range of complex real-world problems across various engineering domains. While exact search methods guarantee an optimal solution, their practicality is often limited when dealing with NP-complete/NP-hard problems due to time constraints. In such cases, heuristic, metaheuristic, and hyperheuristic algorithms become crucial, as they offer near-optimal solutions within a reasonable timeframe, balancing complexity and efficiency. The selection of these algorithms is generally guided by the specific application requirements, including the time available and the desired level of accuracy.
The aim of this Special Issue is to bring together advanced research and innovative applications of heuristics, metaheuristics, and hyperheuristics to address complex optimization problems in engineering. We invite contributions from experts in both academia and industry to showcase recent advancements in optimization algorithms and their applications in solving real-world challenges across diverse engineering fields, including computer, electrical, mechanical, chemical, biomedical, civil, and industrial engineering.
Dr. Mohammad Shokouhifar
Dr. Mehdi Hosseinzadeh
Prof. Dr. Frank Werner
Guest Editors
Manuscript Submission Information
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Keywords
- engineering optimization problems
- heuristic algorithms
- single-solution metaheuristic algorithms
- population-based metaheuristic algorithms
- multi-objective metaheuristic algorithms
- knowledge-based metaheuristic algorithms
- heuristic-driven metaheuristic algorithms
- fuzzy-driven metaheuristic algorithms
- machine learning-driven metaheuristic algorithms
- hyperheuristic algorithms for just-in-time (JIT) problems
- hybrid algorithm design methods
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