E04ABF | Minimum, function of one variable using function values only |

E04BBF | Minimum, function of one variable, using first derivative |

E04CBF | Unconstrained minimization using simplex algorithm, function of several variables using function values only |

E04DGF | Unconstrained minimum, preconditioned conjugate gradient algorithm, function of several variables using first derivatives (comprehensive) |

E04FCF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (comprehensive) |

E04FYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (easy-to-use) |

E04GBF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm using first derivatives (comprehensive) |

E04GDF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (comprehensive) |

E04GYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (easy-to-use) |

E04GZF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (easy-to-use) |

E04HCF | Check user's routine for calculating first derivatives of function |

E04HDF | Check user's routine for calculating second derivatives of function |

E04HEF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (comprehensive) |

E04HYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (easy-to-use) |

E04JCF | Minimum by quadratic approximation, function of several variables, simple bounds, using function values only |

E04JYF | Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using function values only (easy-to-use) |

E04KDF | Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (comprehensive) |

E04KYF | Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using first derivatives (easy-to-use) |

E04KZF | Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (easy-to-use) |

E04LBF | Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (comprehensive) |

E04LYF | Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (easy-to-use) |

E04MFF | LP problem (dense) |

E04MXF | Reads MPS data file defining LP, QP, MILP or MIQP problem |

E04NCF | Convex QP problem or linearly-constrained linear least squares problem (dense) |

E04NFF | QP problem (dense) |

E04NKF | LP or QP problem (sparse) |

E04NQF | LP or QP problem (suitable for sparse problems) |

E04PCF | Computes the least squares solution to a set of linear equations subject to fixed upper and lower bounds on the variables. An option is provided to return a minimal length solution if a solution is not unique |

E04UCF | Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (comprehensive) |

E04UFF | Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (reverse communication, comprehensive) |

E04UGF | NLP problem (sparse) |

E04USF | Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive) |

E04VHF | General sparse nonlinear optimizer |

E04VJF | Determine the pattern of nonzeros in the Jacobian matrix for E04VHF |

E04WDF | Solves the nonlinear programming (NP) problem |

E04XAF | Estimate (using numerical differentiation) gradient and/or Hessian of a function |

E04YAF | Check user's routine for calculating Jacobian of first derivatives |

E04YBF | Check user's routine for calculating Hessian of a sum of squares |

E04YCF | Covariance matrix for nonlinear least squares problem (unconstrained) |

E05SAF | Global optimization using particle swarm algorithm (PSO), bound constraints only |

E05SBF | Global optimization using particle swarm algorithm (PSO), comprehensive |

E05UCF | Global optimization using multi-start, nonlinear constraints |

E05USF | Global optimization of a sum of squares problem using multi-start, nonlinear constraints |

© The Numerical Algorithms Group Ltd, Oxford UK. 2013