public class ActiveSetLineSearchSQP : SequentialQuadraticProgrammingSolver

Public Class ActiveSetLineSearchSQP _
	Inherits SequentialQuadraticProgrammingSolver

public ref class ActiveSetLineSearchSQP : public SequentialQuadraticProgrammingSolver

On each iteration a quadratic subproblem is formed from the Hessian of the Lagrangian and gradient of the objective function evaluated at the current iterate xk. This subproblem is solved using an active set algorithm and its solution yields a step direction, pk for the next iteration. A step size aplhak is then computed using a line search and the next iterate xk+1 is computed as xk+1 = xk + alphak*pk. The iteration is continued until a specified convergence test is passed or a specified maximum number of iterations is exceeded.

Algorithm taken from Numerical Optimization, 2nd Edition, Jorge Nocedal, Stephen J. Wright, ISBN 978-0-387-30303-1, Chapter 18, Algorithm 18.3

System..::.Object
  CenterSpace.NMath.Analysis..::.SequentialQuadraticProgrammingSolver
    CenterSpace.NMath.Analysis..::.ActiveSetLineSearchSQP