Optimization Software Guide
Developments in optimization theory, including emphasis on large problems and on interior-point methods for linear programming, have begun to appear in production software. Here is a reference tool that includes discussions of these areas and names software packages that incorporate the results of theoretical research. After an introduction to the major problem areas in optimization and an outline of the algorithms used to solve them, a data sheet is presented for each of the 75 software packages and libraries in the authors' survey. These include information on the capabilities of the packages, how to obtain them, and addresses for further information. Standard optimization paradigms are addressed - linear, quadratic, and nonlinear programming; network optimization; unconstrained and bound-constrained optimization; least-squares problems; nonlinear equations; and integer programming. The most practical algorithms for the major fields of numerical optimization are outlined, and the software packages in which they are implemented are described.
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active set Additional comments ANSI approximation Areas covered augmented Lagrangian BFGS bound-constrained problems bounds codes components computing conjugate gradient Contact address convergence CPLEX direction dº double-precision environment The software Fortran 77 GAMS Gauss–Newton GRG2 Hardware/software environment Software Hessian matrix implemented IMSL integer interface iteration Jacobian matrix LANCELOT large-scale problems least squares problems Levenberg–Marquardt LINDO line-search linear algebra linear least squares linear programming problems LSSOL Math Mathematics MATLAB merit function MINOS mixed-integer netlib network optimization Newton's method NLPQL node nonlinear equations nonlinear least squares nonlinear programming NPSOL number of variables objective function obtained optimization problems package parameters Phone PROC NLP QPOPT quasi-Newton methods References routines search direction sequential quadratic programming simplex algorithm simplex method Software is written solution solve solvers sparse strategy subproblem subroutine techniques truncated Newton unconstrained minimization unconstrained optimization update User’s vector workstations written in ANSI