In this section, we describe the framework for a bound-constrained minimization problem.
Once you have mastered bound-constrained objects and setting up the objective function, it is a simple 2-step process to build a bound-constrained nonlinear problem.
Let's consider the two-dimensional Rosenbrock problem with bounds on the variables:
Step 1: Build your bound constraint.
int ndim = 2;
ColumnVector lower(ndim), upper(ndim);
lower = -2.0; upper = 2.0;
Constraint bc = new BoundConstraint(ndim, lower, upper);
Step 2: Create a constrained NLF1 object.
OPT++ contains no less than six solvers for bound-constrained optimization problems. To name a few, there are implementations of Newton's method, barrier Newton's method, interior-point methods, and direct search algorithms. We provide examples of solving the bound-constrained Rosenbrock problem with an active set strategy and a nonlinear interior-point method.
Bound-constrained Quasi-Newton method with line-search
Finite-difference nonlinear interior-point method with line-search
Next Section: Constrained minimization | Back to Solvers Page
Last revised July 13, 2006
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Documentation, generated by , last revised August 30, 2006.