Sentence examples for multimodal objective function from inspiring English sources

The uniform design technique is incorporated into the revised Hooke Jeeves algorithm to handle the multimodal objective function.

The co-existence of discrete and continuous independent variables in an engineering optimization problem with a multimodal objective function makes many methods incapable of solving the problem.

A Genetic Algorithm is employed to determine the global minimal solution to the multimodal objective function, which can be difficult to achieve by traditional gradient-directed search methods.

A dynamic combination scheme of genetic operators is formulated to explore and exploit the FPGA in the non-convex solution space and multimodal objective function.

Aspects of such challenge include large search space dimensionality, absence of a closed-form objective function (OF) and constraints, multimodal objective function and costly CPU time per objective function evaluation.

If and when the presence of multimodal objective function is confirmed from multistart local optimizations (typically involving 25-50 initial guesses), a hybrid stochastic-local optimization method such as the scatter search based approach should be used.

The modified method is able to optimize complex and multimodal objective functions.

Differential evolution is a novel evolutionary approach capable of handling non-differentiable, nonlinear and multimodal objective functions.

Problems with highly nonlinear, or multimodal, objective functions are extremely difficult to solve and are further complicated by the presence of multiple objectives.

Differential evolution (DE), one of the evolutionary algorithms, is a novel optimization method capable of handling nondifferentiable, non-linear and multimodal objective functions.

Yang and Deb (2009) added that the primary reasons for such performance of the CS algorithm are the fine balance of randomization and intensification and the fact that fewer parameters are to be fine-controlled, which makes it evidently better and efficient for multimodal objective functions.