A Metaheuristic Optimization Algorithm refers to a family of methods used in computer science that aim to find a global optimum by repeatedly evaluating the objective function without relying on gradient inform
Metaheuristic Optimization Algorithms have become indispensable tools, with applications in data analysis, text mining, classification problems, computer vision, image analysis, pattern recognition, medicine, and many others. Most complex systems problems involve a continuous flow of data that makes it ...
Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applicationspresents the most recent optimization algorithms and their applications across a wide range of scientific and engineering research fields. The book provides readers with a comprehensive overview of eighteen optimization algorithms to add...
Over recent years, numerous metaheuristic optimization algorithms (MOAs) have surfaced for addressing the MAED problem. However, none of the literature to date conducted a comprehensive statistical research work on the MAED problem. In part I of this series, we present a comprehensive survey on ...
Empty CellCharacteristicsOptimized objectsMetaheuristic optimization algorithms Single-objective Advantages: • Easy to implement • EfficientDisadvantage: • Relatively low ability Combination weights BA [143], B_WCA [132], CLSFPA [33], AFSA-ACO [136], GWO [135] Parameters in predictors BA [83...
Post-processing is conducted on the measured impedance data using four metaheuristic optimization algorithms to extract the parameters of the employed models. The applied algorithms are adopted according to the literature, where they proved to output satisfying results. It is essential to precisely define...
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The simulation-driven metaheuristic algorithms have been successful in solving numerous problems compared to their deterministic counterparts. Despite this
Metaheuristic algorithms are proposed to meet such a need. A metaheuristic algorithm is a stochastic optimization algorithm. As such, it combines a stochastic method with a local search method. Compared with deterministic algorithms, metaheuristic algorithms have attracted considerable attention owing to ...
such as gravitational search algorithm[138], and charged system search[139,140]can be used for the parameter identification of parametric hysteresis model. There parameter identification is an open problem. Better optimal solutions can be obtained with the development of optimization algorithms. ...