[PDF] from cc.ac.cnX Liu… - SIAM Journal on Optimization, 2011 - link.aip.org We present a sequential quadratic programming method without using a penalty function or a filter for solving nonlinear equality constrained optimization. In each iteration, the linearized constraints of the quadratic programming are relaxed to satisfy two mild conditions; the step-size is ... Related articles - All 9 versions
Q Liu… - Neurocomputing, 2011 - Elsevier Constrained quadratic programming has many applications in scientific and engineering areas, such as signal and image processing, manufacturing, optimal control, and pattern recognition. Over the past years, a variety of numerical algorithms have been developed ... Related articles
[PDF] from optimization-online.orgJ Chen… - 2011 - optimization-online.org Abstract Nonconvex quadratic programming (QP) is an NP-hard problem that optimizes a general quadratic function over linear constraints. This paper introduces a new global optimization algorithm for this problem, which combines two ideas from the literature—finite branching based on ... Related articles - View as HTML
[PDF] from optimization-online.orgC Kirches, HG Bock, JP Schlöder… - Optimization Methods & …, 2011 - Taylor & Francis In this contribution, we address the efficient solution of optimal control problems of dynamic processes with many controls. Such problems arise, for example, from the outer convexification of integer control decisions. We treat this optimal control problem class using the direct multiple ... Cited by 6 - Related articles - All 5 versions
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