However, classical optimization tools are often too computationally demanding to be considered satisfactory. This has motivated the application of metaheuristic methods, which offer a good compromise in terms of solution quality and computation time. However, these methods have been applied in an ...
Metaheuristic Algorithms: These algorithms are higher-level procedures that guide other algorithms in exploring the search space effectively. They are particularly useful for complex routing problems where finding an optimal solution is computationally expensive. Examples include: Genetic Algorithms Simulated An...
This prompted some researchers to focus on optimizing contractors' operational decisions using linear programming models (Tirkolaee et al., 2021; Tirkolaee and Aydın, 2021) and metaheuristic algorithms (Liu et al., 2020). The results can help contractors to a better plan. Valizadeh and ...
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Design of Optimal QFT Controller and Prefilter for Buck Converter Using Metaheuristic Algorithms Phlebotomy occurred at 4 time points--baseline, 6 months, 12 months, and 18 months--and QFT, T-SPOT, and TST were performed as per the study protocol on the enrolled HCWs [9,10]. Influence of...
Second, the decision- making processes of AI are increasingly mirroring our own, as demonstrated by the current advancements in AI, where deep learning algorithms are capable of accomplishing tasks traditionally carried out by humans. Third, there is a bur- geoning reliance on AI for decision-...
(Terken & Lemeer, 1988), but we chose to use syntheticf0contours over natural ones to make sure that the suprasegmental aspect of the synthetic syllables also came from stochastic-optimisation-based vocal learning algorithms.2The audio files were synthesised with a sampling rate of 44.1 kHz and...
The solutions of finest individuals found by mentioned algorithms are given in Table 2 Case I column with respect to best, worst, and average solution (of 35 simulations) along with the result of mixed-integer nonlinear programming (MINLP), small population based PSO, and improved DE published ...
However, classical optimization tools are often too computationally demanding to be considered satisfactory. This has motivated the application of metaheuristic methods, which offer a good compromise in terms of solution quality and computation time. However, these methods have been applied in an ...
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