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Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization
IEEE Transactions on Evolutionary Computation, 2009A. K. Qin, V. L. Huang, P. Suganthan
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Numerical Optimization Techniques
1987Numerical optimization techniques provide a uniquely general and versatile tool for design automation. While these methods have been developed, to a large degree, by the operations research community, research in their application to engineering problems has been extensive as well.
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Optimally Stable Lagrangian Numerical Differentiation
SIAM Journal on Numerical Analysis, 1975Approximating a derivative of a function at a point by the corresponding derivative of its interpolating polynomial is called Lagrangian numerical differentiation. In this work we describe the nodes at which to interpolate in order to minimize the error in Lagrangian numerical differentiation due to errors in the sampled values of the function.
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Numerical Optimization Methods
2015In this chapter we present and analyze some infinite dimensional optimization methods for the solution of problem (.1). Once the infinite dimensional algorithm is posed, the discretization of the partial differential equations is carried out. Such an approach is known as optimize-then-discretize in contrast to the discretize-then—optimize one, where ...
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Numerical methods for unconstrained optimization and nonlinear equations
Prentice Hall series in computational mathematics, 1983J. Dennis, Bobby Schnabel
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An adaptive differential evolution with combined strategy for global numerical optimization
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2019Gaoji Sun +3 more
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