Abstract. We examine the local convergence properties of pattern search methods, complementing the previously established global convergence properties for this class of algorithms. We show that the step-length control parameter which appears in the definition of pattern search algorithms provides a reliable asymptotic measure of first-order stationarity. This gives an analytical justification for a traditional stopping criterion for pattern search methods. Using this measure of first-order stationarity, we both revisit the global convergence properties of pattern search and analyze the behavior of pattern search in the neighborhood of an isolated local minimizer
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms ...
We extend pattern search methods to linearly constrained minimization. We develop a general class of...
Abstract. We present a convergence theory for pattern search methods for solving bound constrained n...
We examine the local convergence properties of pattern search methods, complementing the previously ...
Abstract. We examine the local convergence properties of pattern search methods, complementing the p...
We examine the local convergence properties of pattern search methods, complementing the previously ...
. This paper gives a unifying, abstract generalization of pattern search methods for solving nonline...
Abstract. The convergence theory of generalized pattern search algorithms for unconstrained optimiza...
In this paper the authors prove global convergence for asynchronous parallel pattern search. In stan...
Previous analyses of pattern search algorithms for unconstrained and linearly constrained minimizati...
Recently, general definitions of pattern search methods for both unconstrained and linearly constrai...
Abstract. This paper contains a new convergence analysis for the Lewis and Torczon GPS class of patt...
Abstract. Previous analyses of pattern search algorithms for unconstrained and linearly constrained ...
The definition of pattern search methods for solving nonlinear unconstrained optimization problems i...
This paper contains a new convergence analysis for the Lewis and Torczon generalized pattern search ...
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms ...
We extend pattern search methods to linearly constrained minimization. We develop a general class of...
Abstract. We present a convergence theory for pattern search methods for solving bound constrained n...
We examine the local convergence properties of pattern search methods, complementing the previously ...
Abstract. We examine the local convergence properties of pattern search methods, complementing the p...
We examine the local convergence properties of pattern search methods, complementing the previously ...
. This paper gives a unifying, abstract generalization of pattern search methods for solving nonline...
Abstract. The convergence theory of generalized pattern search algorithms for unconstrained optimiza...
In this paper the authors prove global convergence for asynchronous parallel pattern search. In stan...
Previous analyses of pattern search algorithms for unconstrained and linearly constrained minimizati...
Recently, general definitions of pattern search methods for both unconstrained and linearly constrai...
Abstract. This paper contains a new convergence analysis for the Lewis and Torczon GPS class of patt...
Abstract. Previous analyses of pattern search algorithms for unconstrained and linearly constrained ...
The definition of pattern search methods for solving nonlinear unconstrained optimization problems i...
This paper contains a new convergence analysis for the Lewis and Torczon generalized pattern search ...
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms ...
We extend pattern search methods to linearly constrained minimization. We develop a general class of...
Abstract. We present a convergence theory for pattern search methods for solving bound constrained n...