# Keyword : Optimization

 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