Dear Colleagues,

Solution search methods for solving optimization problems can be categorized into exact, knowledge-based heuristic, and random-based meta-heuristic algorithms. Although exact search methods consistently achieve an optimal solution, such practices are not applicable to complex engineering problems that belong to the class of NP-complete/hard problems.

Over the past few years, various heuristic, meta-heuristic, and hyper-heuristic optimization algorithms have been introduced and applied to tackle the complexities of real-world engineering problems. Heuristics are high-speed application-specific methods, but they do not effectively investigate the search space. In contrast, meta-heuristics can obtain higher quality solutions due to their ability to cope with high computational complexity. As an extension to heuristics, hyper-heuristics provide agile and high-quality solutions that are capable of changing from one application variant to a new one quickly, which is important for solving real-time engineering problems.

This Special Issue aims to report the recent advances in optimization methods from theoretical, methodological, and applied viewpoints. We invite researchers and participants from academia and industry to submit their original research and review articles concerning new and existing heuristics, meta-heuristics, and hyper-heuristics for solving optimization problems in different branches of engineering.

Dr. Mohammad Shokouhifar
Prof. Dr. Frank Werner
Dr. Laith Abualigah
Prof. Dr. Seyedali Mirjalili
Guest Editors

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• engineering optimization
• mathematical modeling
• combinatorial optimization
• robust optimization
• exact methods
• heuristic algorithms
• meta-heuristic algorithms
• hyper-heuristic algorithms
• evolutionary computation
• swarm intelligence
• local-search algorithms
• multi-objective optimization
• constraint handling methods
• hybrid optimization methods
• fuzzy sets and systems
• machine learning
• deep learning
• graph theory and applications
• scheduling problems
• resource allocation problems
• vehicle routing problems
• big-data analytics
• signal/image processing
• manufacturing systems
• chemical processes
• Internet-of-Things