Optimization is central to any problem involving decision making. The area of optimization has received enormous attention for over 30 years and it is still popular in research field to this day. In this paper, a global optimization method called Improved Homotopy with 2-Step Predictor-corrector Method will be introduced. The method in- troduced is able to identify all local solutions by converting non-convex optimization problems into piece-wise convex optimization problems. A mechanism which only consid- ers the convex part where minimizers existed on a function is applied. This mechanism allows the method to filter out concave parts and some unrelated parts automatically. The identified convex parts are called trusted intervals. The desc...
124 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.Finally, in a complementary l...
A quadratically convergent line-search algorithm for piecewise smooth convex optimization based on a...
Many engineering optimization problems can be formulated as nonconvex nonlinear pro-gramming problem...
Optimization is central to any problem involving decision making. The area of optimization has recei...
A class of nonconvex minimization problems can be classified as hidden convex minimization problems....
Convexity is, without a doubt, one of the most desirable features in optimization. Many optimization...
A class of convexification and concavification methods are proposed for solving some classes of non-...
Global search algorithm, Local search algorithm, Nonconvex optimization, Convex maximization, Piecew...
This paper presents a new method for global optimization. We use exact quadratic regularization for ...
International audienceFor dealing with sparse models, a large number of continuous approximations of...
This book presents state-of-the-art results and methodologies in modern global optimization, and has...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
AbstractA global optimization algorithm is proposed in order to locate the global minimum of the spe...
International audienceMany important classes of decision models give rise to the problem of finding ...
We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method ...
124 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.Finally, in a complementary l...
A quadratically convergent line-search algorithm for piecewise smooth convex optimization based on a...
Many engineering optimization problems can be formulated as nonconvex nonlinear pro-gramming problem...
Optimization is central to any problem involving decision making. The area of optimization has recei...
A class of nonconvex minimization problems can be classified as hidden convex minimization problems....
Convexity is, without a doubt, one of the most desirable features in optimization. Many optimization...
A class of convexification and concavification methods are proposed for solving some classes of non-...
Global search algorithm, Local search algorithm, Nonconvex optimization, Convex maximization, Piecew...
This paper presents a new method for global optimization. We use exact quadratic regularization for ...
International audienceFor dealing with sparse models, a large number of continuous approximations of...
This book presents state-of-the-art results and methodologies in modern global optimization, and has...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
AbstractA global optimization algorithm is proposed in order to locate the global minimum of the spe...
International audienceMany important classes of decision models give rise to the problem of finding ...
We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method ...
124 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.Finally, in a complementary l...
A quadratically convergent line-search algorithm for piecewise smooth convex optimization based on a...
Many engineering optimization problems can be formulated as nonconvex nonlinear pro-gramming problem...