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Needle insertions are simulated and regarded as evaluations of the objective function by the iterative planning process.
Topology optimization problem requires repeated evaluations of the objective function and design sensitivity in the design domain with various density distributions.
This model allows the identification of the influential parameters of an optimisation problem and the reduction of the number of evaluations of the objective function.
The numerical results obtained show that the optimal stacking sequences are determined with fewer evaluations of the objective function than might be expected from considerations of the size of the design space.
Due to the objective function f(β γ (n) + (1 − β p (n − 1)) in step (3) of Algorithm AWCR being (upper) convex, i.e., being concave, in the scalar variable β, for computing the maximum solution to the corresponding optimization problem, we can choose finite searching steps with even fewer evaluations of the objective function.
These methods rely extensively on repeated evaluations of the objective function and use heuristic guidelines for estimating the next search direction.
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The proposed method applies comparison to judge whether or not a new child is worth evaluating, so that the evaluation of the objective function can be skipped.
The algorithm is repeated from the point of evaluation of the objective function for all particles and for iterations.
These parameters are required during the evaluation of the objective function for each particle in all iterations.
It is used for the evaluation of the objective value, and no further structural information is used.
The following section contains the results of the evaluation of the objective full-reference assessment algorithms against the databases with subjective test data.
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