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Nature-inspired firefly algorithm (FA) based optimization is employed to search for optimal controller parameters and governor speed regulation parameters simultaneously.
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In this view, a method based on local optimization is employed to achieve the best solution [3].
Simulation based optimization are extensively employed to enrich the performance of the inferior nodes close to achievable benchmark standards by minimizing the supply chain cost.
Two types of optimization methods, reliability based design optimization and possibility based design optimization, are employed to identify the optimal design considering objective random uncertainties and subjective fuzzy uncertainties.
To train the SVR model on these datasets cross-validation and parameter optimization are employed.
Extremum seeking, a non-model based optimization scheme, is employed to design laser pulse shapes that maximize the amount of stored energy extracted from the amplifier gain medium for a fixed input energy and inversion density.
Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems.
Therefore if local optimality criteria based optimization algorithms are employed to find the worst case structural responses that are used for examining the feasibility of a given design, it is highly possible that the optimization process will get stuck in a local optimum.
In [66], a novel HOA algorithm, called biogeography based optimization (BBO) was employed to solve constrained OPF problems in power systems with the consideration of valve point nonlinearities of generators.
Some optimizations are employed, e.g. to restrict the search space for matching reactants.
In this paper, a novel teaching-learning based optimization (TLBO) approach is employed to design ultra-low reflective coating over a broad wavelength-band using multilayer thin-film structures for optoelectronic devices.
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