Class ADMMQPOptimizer


public class ADMMQPOptimizer extends QPOptimizer
Alternating Direction Method of Multipliers Quadratic Programming Optimizer. \[ min \frac{1}{2} X^T Q X + G X a\\ A X = B_1\\ B X \ge B_2\\ l_b \le C X \le u_b \] Algorithm based on paper:"An Operator Splitting Solver for Quadratic Programs(Bartolomeo Stellato, Goran Banjac, Paul Goulart, Alberto Bemporad, Stephen Boyd,February 13 2020)"
Since:
3.1
  • Constructor Details

    • ADMMQPOptimizer

      public ADMMQPOptimizer()
      Simple constructor.

      This constructor sets all options to their default values

  • Method Details

    • getConvergenceChecker

      public ConvergenceChecker<LagrangeSolution> getConvergenceChecker()
      Gets the convergence checker.
      Overrides:
      getConvergenceChecker in class BaseOptimizer<LagrangeSolution>
      Returns:
      the object used to check for convergence.
    • optimize

      public LagrangeSolution optimize(OptimizationData... optData)
      Stores data and performs the optimization.

      The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.

      When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

      Important note: Subclasses must override BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

      Overrides:
      optimize in class ConstraintOptimizer
      Parameters:
      optData - Optimization data. In addition to those documented in BaseOptimizer, this method will register the following data:
      Returns:
      a point/value pair that satisfies the convergence criteria.
    • parseOptimizationData

      protected void parseOptimizationData(OptimizationData... optData)
      Scans the list of (required and optional) optimization data that characterize the problem.
      Overrides:
      parseOptimizationData in class BaseMultivariateOptimizer<LagrangeSolution>
      Parameters:
      optData - Optimization data. The following data will be looked for:
    • doOptimize

      public LagrangeSolution doOptimize()
      Performs the bulk of the optimization algorithm.
      Overrides:
      doOptimize in class QPOptimizer
      Returns:
      the point/value pair giving the optimal value of the objective function.
    • isConverged

      public boolean isConverged()
      Check if convergence has been reached.
      Returns:
      true if convergence has been reached