BzzConstrainedMinimization class

In the BzzConstrainedMinimization class, an object of the BzzMinimi-zationMultiVeryRobust class is used in unison with other algorithms in the initial phase of the search for small dimension problems. 

A BzzConstrainedMinimization class object is similar to a matryoshka It solves a problem of a certain level using objects from the lower levels. In some circumstances, the same object can use objects from other classes to solve special subproblems. 

The role of objects H and P of the BzzMatrixSparseLoclced class as well as of nlH and nlP of the nlBzzVectorlnt class in the definition of an object of the BzzConstrainedMinimization class with sparse matrices is to allow the use of the following functions. 

In an object from the BzzConstrainedMinimization class with sparse systems, two BzzVectorint objects, nlH and nlP, are used to indicate which variables are really nonlinear in the nonlinear equality or inequality constraints. They are necessary to efficiently update the Jacobians and the Hessians of the functions of constraints. 

In the BzzConstrainedMinimization class, the linearization of the function and constraints is obviously used when the function and constraints are linear, but also as alternative in higher level problems. 

In the BzzConstrainedMinimization class the LQ factorization is used in small-medium dense problems. 

In the BzzConstrainedMinimization class, the new point obtained with Xi+i = Xi + di is accepted if either the merit function i or the function (13.88) decrease. However, the options described in Chapter 3 for unconstrained optimization are adopted. 

In the BzzConstrainedMinimization dass, a BzzOptnov class object is used when the selected algorithm provides a prediction that is worse than the original point even though the constraints are reasonably well fulfilled. 

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