Class SQPActiveSetMinimizer.Solution

    • Method Detail

      • setInitials

        public void setInitials​(Vector... initials)
        Supply the starting points for the search. This can also initialize the state of the algorithm for a new search.
        Specified by:
        setInitials in interface IterativeMethod<Vector>
        Parameters:
        initials - x0 s.t., \(c_j(x_0) \geq 0, j = 1, 2, ..., q\); λ0, the Lagrange multipliers for equality constraints (lambda); μ0 &ge 0, the Lagrange multipliers for inequality constraints (mu)
      • search

        public Vector search​(Vector... initials)
                      throws Exception
        Search for a solution that optimizes the objective function from the given starting points. This method typically calls first #setInitials(S...) and then iteratively IterativeMethod.step(). It implements a default convergence criterion.
        Specified by:
        search in interface IterativeMethod<Vector>
        Parameters:
        initials - x0 s.t., \(c_j(x_0) \geq 0, j = 1, 2, ..., q\); λ0, the Lagrange multipliers for equality constraints (lambda); μ0 &ge 0, the Lagrange multipliers for inequality constraints (mu)
        Returns:
        an (approximate) optimizer
        Throws:
        Exception
      • search

        public Vector search​(Vector x0)
                      throws Exception
        Search for a solution that minimizes the objective function from the given starting point.
        Parameters:
        x0 - an initial guess s.t., \(c_j(x_0) \geq 0, j = 1, 2, ..., q\)
        Returns:
        an (approximate) optimizer
        Throws:
        Exception - when an error occurs during the search
      • search

        public Vector search​(Vector x0,
                             Vector lambda0,
                             Vector mu0)
                      throws Exception
        Search for a solution that minimizes the objective function from the given starting point. Note that f(x0) ≥ 0 and μ0 ≥ 0
        Parameters:
        x0 - x0 s.t., \(c_j(x_0) \geq 0, j = 1, 2, ..., q\)
        lambda0 - λ0, the Lagrange multipliers for equality constraints (lambda)
        mu0 - μ0 &ge 0, the Lagrange multipliers for inequality constraints (mu)
        Returns:
        an (approximate) minimizer
        Throws:
        Exception - when an error occurs during the search