Real-World Applications of Metaheuristic Algorithms: A Comprehensive Review of the State-of-the-Art
DOI:
https://doi.org/10.24237/djes.2024.18201Keywords:
Optimization, Metaheuristic, Engineering optimization, Nature inspired, Swarm-basedAbstract
Metaheuristic algorithms have gained significant acceptance in large areas of optimization, giving unique and novel solutions to complicated problems across various areas. This research dives into the wide classification of state-of-the-art real-world applications that depend on metaheuristic algorithms, acknowledging their prevalence and the diversity of real-world applications where their performances are evaluated. The major goal is to evaluate forty-eight metaheuristic algorithms from 2020 to 2024 based on the results presented in their original research articles, emphasizing their effectiveness in tackling six prevalent real-world applications. In addition, the study classifies the algorithms and compares them to determine which ones are most effective for the particular applications. The results point out the necessity to solve the actual problems using opting for a metaheuristic algorithm. Nevertheless, it becomes very obvious that no algorithm works well in all the cases pointed out, as a demand for an informed selection based on the task complexity. This research contributes to the ongoing development and application of metaheuristic algorithms in diverse practical settings by providing valuable insights into the dynamic landscape of metaheuristics.
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