The development of recent engineering systems has introduced increasing levels of complexity and uncertainty over time. Combined with the planning philosophy of engineering itself, this has given rise to several studies addressing the straightforward or multi-objective optimization problems present in these complex systems. Although conventional approaches are often applied to engineering optimization depends largely on the character of problem, but they suffered to supply some quick and reasonable feedback to designers and cannot be challenging to further possible problems. However, researchers prefer quasi-Newton methodsto solve the unconstrained non-linear optimization problems, using updating the approximation to the inverse Hessian. This technique is a computationally expensive operation and, therefore, in this paper we investigate the possibility of skipping update of Hessian approximation on every second step. The experimental results show that the new methods (i.e. with skipping) give better performance in general than existing two-step methods, particularly as the dimension of the test problem increases.
Nudrat Aamir John Ford “Two-Step Skipping Techniques For Solution of Nonlinear UnconstrainedOptimization International Journal of Engineering Works Vol. 8 Issue 06 PP. 170-174 June 2021 https://doi.org/10.34259/ijew.21.806170174.
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