article · Archives of Computational Methods in Engineering
Rapid computational advances require effective problem-solving techniques that deliver optimal global solutions under varying restrictions. Metaheuristic algorithms offer significant advantages over alternative methods across diverse problem classes. A detailed review establishes an overview of these techniques by examining their fundamental nature, distinct types, applications, and ongoing challenges. Algorithms are classified according to several dimensions, including their source of inspiration, the number of search agents employed, the mechanisms agents use to update their positions, and the count of primary parameters. Alongside an exploration of the structure and types of optimization problems, the review presents the most common practical application areas. It also evaluates key open challenges to outline future research trajectories, serving as an orienting framework for both experienced investigators and new entrants seeking active problems within the optimization landscape.
Complex optimization challenges arise continuously in computing and engineering, where finding an optimal global balance among competing constraints is difficult. By categorising diverse metaheuristic approaches and examining their operational mechanisms, this synthesis equips researchers and computational practitioners with a structured map to select suitable algorithmic approaches and identify unsolved problems across technical systems.
While the abstract highlights that widely used applications of metaheuristic algorithms are reviewed, it does not specify particular commercial sectors, end-users, or technology readiness levels. The work represents early-stage, secondary academic research designed to structure algorithmic knowledge and guide future theoretical inquiry rather than deliver a tested, market-ready tool.
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Abstract The greatest and fastest advances in the computing world today require researchers to develop new problem-solving techniques capable of providing an optimal global solution considering a set of aspects and restrictions. Due to the superiority of the metaheuristic Algorithms (MAs) in solving different classes of problems and providing promising results, MAs need to be studied. Numerous studies of MAs algorithms in different fields exist, but in this study, a comprehensive review of MAs, its nature, types, applications, and open issues are introduced in detail. Specifically, we introduce the metaheuristics' advantages over other techniques. To obtain an entire view about MAs, different classifications based on different aspects (i.e., inspiration source, number of search agents, the updating mechanisms followed by search agents in updating their positions, and the number of primary parameters of the algorithms) are presented in detail, along with the optimization problems including both structure and different types. The application area occupies a lot of research, so in this study, the most widely used applications of MAs are presented. Finally, a great effort of this research is directed to discuss the different open issues and challenges of MAs, which help upcoming researchers to know the future directions of this active field. Overall, this study helps existing researchers understand the basic information of the metaheuristic field in addition to directing newcomers to the active areas and problems that need to be addressed in the future.
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DOI: 10.1007/s11831-024-10168-6
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