More test examples for nonlinear programming codes
More test examples for nonlinear programming codes
Global convergence and stabilization of unconstrained minimization methods without derivatives
Journal of Optimization Theory and Applications
Recent progress in unconstrained nonlinear optimization without derivatives
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
On the Convergence of Pattern Search Algorithms
SIAM Journal on Optimization
Pattern Search Algorithms for Bound Constrained Minimization
SIAM Journal on Optimization
Fortified-Descent Simplicial Search Method: A General Approach
SIAM Journal on Optimization
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Derivative-free methods for bound constrained mixed-integer optimization
Computational Optimization and Applications
A gradient method for unconstrained optimization in noisy environment
Applied Numerical Mathematics
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In this work, we propose a new globally convergent derivative-free algorithm for the minimization of a continuously differentiable function in the case that some of (or all) the variables are bounded. This algorithm investigates the local behaviour of the objective function on the feasible set by sampling it along the coordinate directions. Whenever a “suitable” descent feasible coordinate direction is detected a new point is produced by performing a linesearch along this direction. The information progressively obtained during the iterates of the algorithm can be used to build an approximation model of the objective function. The minimum of such a model is accepted if it produces an improvement of the objective function value. We also derive a bound for the limit accuracy of the algorithm in the minimization of noisy functions. Finally, we report the results of a preliminary numerical experience.