java.lang.Object
dev.nm.solver.multivariate.constrained.convex.sdp.pathfollowing.CSDPMinimizer.Solution
All Implemented Interfaces:
IterativeMethod<CentralPath>, IterativeSolution<CentralPath>, MinimizationSolution<CentralPath>
Enclosing class:
CSDPMinimizer

public class CSDPMinimizer.Solution extends Object implements IterativeSolution<CentralPath>
  • Method Details

    • 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 IterativeMethod.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
    • step

      public Boolean step()
      Description copied from interface: IterativeMethod
      Do the next iteration.
      Specified by:
      step in interface IterativeMethod<CentralPath>
      Returns:
      false when the iteration should stop
    • svecA

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

      public double minimum()
      Description copied from interface: MinimizationSolution
      Get the (approximate) minimum found.
      Specified by:
      minimum in interface MinimizationSolution<CentralPath>
      Returns:
      the (approximate) minimum found
    • minimizer

      public CentralPath minimizer()
      Description copied from interface: MinimizationSolution
      Get the minimizer (solution) to the minimization problem.
      Specified by:
      minimizer in interface MinimizationSolution<CentralPath>
      Returns:
      the minimizer