Class CSDPMinimizer.Solution

    • Method Detail

      • search

        public CentralPath search​(CentralPath... initials)
        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<CentralPath>
        Parameters:
        initials - initial values (one value only)
        Returns:
        an (approximate) optimizer
      • search

        public CentralPath search()
        Searches for a solution that optimizes the objective function from the default starting points.
        Returns:
        an (approximate) optimizer
      • search

        public CentralPath search​(CentralPath initial)
        Search for a solution that optimizes the objective function from the given starting points.
        Parameters:
        initial - an initial value
        Returns:
        an (approximate) optimizer
      • setInitials

        public void setInitials​(CentralPath... initials)
        Description copied from interface: IterativeMethod
        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<CentralPath>
        Parameters:
        initials - the initial guesses
      • svecA

        protected Matrix svecA()
        Returns:
        a k by n*(n+1)/2 matrix, the i-th row is svec(problem.A(i)).