Minimisation

The routines for minimisation (or optimisation) in this library are:

• PDA_DNLS1
  Minimises the sum of squares of M non-linear functions.

• PDA_DNLS1E
  Minimises the sum of squares of M non-linear functions (easy version).

• PDA_DQED
  Solve bounded nonlinear least squares and nonlinear equations.

• PDA_LMDIF1 (MINPACK/NETLIB)
  Minimise the sum of the squares of m nonlinear functions in n variables, simple interface to PDA_LMDIF.

• PDA_LMDIF (MINPACK/NETLIB)
  Minimise the sum of the squares of m nonlinear functions in n variables with a modified Levenberg-Marquardt algorithm. Needs function only, the Jacobian is calculated by a forward-difference approximation.

• PDA_UNCMND (NMS/TIBER)
  Minimises a smooth non-linear function of n variables. Needs function values only.

• PDA_SA (module SIMANN from OPT/NETLIB)
  Continuous simulated annealing global optimisation algorithm. Simple constraints can be specified.

• PDA_SUMSL (module SUMSL from TOMS)
  Minimises a general unconstrained objective function using analytic gradients and a hessian approximation from secant update.

• PDA_SUBPLX (module SUBPLEX from OPT/NETLIB)
  Subplex method to solve unconstrained optimisation problems. The method is well suited for optimising objective functions that are noisy or are discontinuous at the solution.