Recent advances in neural-network architecture allow for seamless integration of convex optimization problems as differentiable layers an end-to-end trainable neural network. Integrating medium and large scale quadratic programs into a deep network architecture, however, is challenging solving exactly by interior-point methods has worst-case cubic complexity the number variables. In this paper,...

We compare and contrast a number of recent sequential quadratic programming (SQP) methods that have been proposed for the solution of large-scale nonlinear programming problems. Both line-search and trust-region approaches are considered, as are the implications of interior-point and quadratic programming methods.

This paper presents a new practical approach to complex quadratic programming which solves the broad class of complex approximation problems employing finitization of semi-infinite formulations. The approximation problem may be general with arbitrarily complex basis functions. By using a new technique, the associated semi-infinite quadratic programming problem can be solved taking advantage of ...

We propose and analyze a perturbed version of the classical Josephy-Newton method for solving generalized equations, and of the sequential quadratic programming method for optimization problems. This perturbed framework is convenient to treat in a unified way standard sequential quadratic programming, its stabilzed version [9, 2], sequential quadratically constrained quadratic programming [1, 4...

The Vertex Separator Problem (VSP) for a graph is to find the smallest collection of vertices whose removal breaks the graph into two disconnected subsets of roughly equal size. In a recent paper (Optimality Conditions For Maximizing a Function Over a Polyhedron, Mathematical Programming, 2013, doi: 10.1007/s10107-013-0644-1), the authors announced a new continuous bilinear quadratic programmin...

This paper presents priority based fuzzy goal programming approach to multi-objective quadratic programming problem. In the proposed approach, we construct the quadratic membership functions by determining the individual best solution of the objective functions subject to the system constraints. The quadratic membership functions are then transformed into equivalent linear membership functions ...