MINOS
| Extended name | Modular Incore Nonlinear Optimization System |

Authors | Bruce A. Murtagh
Graduate School of Management, Macquarie University, Sydney, NSW 2109, Australia Michael Saunders | |

Language | Fortran 77 | |

Algorithm | MINOS solves a sequence of subproblems in which the constraints are linearized and the objective is an augmented Lagrangian (involving all nonlinear functions). | |

Input Format | Optional data input from MPS files.
May be called from a driver program, typically in Fortran, C or MATLAB | |

Modeling Languages link | GAMS, AMPL, Matlab and CUTE interfaces available. | |

Commercial Status | Licensing Contact:
Hans Wiesendanger, Licensing Associate, Stanford University Office of Technology Licensing E-Mail: hans@otlmail.stanford.edu Phone: (650) 723-0692 | |

Platform | Any machine with a reasonable amount of memory and a Fortran compiler. | |

Remarks | MINOS is a software package for solving large-scale optimization problems (linear and nonlinear programs). With sufficient memory, MINOS can process large linear programming models similar to those solved by commercial systems such as CPLEX and OSL. It is especially effective for problems with a smooth nonlinear objective function and sparse linear constraints (e.g., quadratic programs). MINOS can also process large numbers of smooth nonlinear constraints. The functions need not be convex.
Numerically stable algorithms. Needs only first derivatives. Warm start capability. MINOS is highly effective for problems with a nonlinear objective function and large numbers of sparse linear constraints (as well as bounds on the variables). | |

References | B. A. Murtagh and M. A. Saunders, Large-scale linearly constrained optimization, Mathematical Programming 14, 41-72 (1978).
B. A. Murtagh and M. A. Saunders, A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints, Mathematical Programming Study 16 Constrained Optimization), 84-117 (1982). B. A. Murtagh and M. A. Saunders, MINOS 5.5 User's Guide, Report SOL 83-20R, Systems Optimization Laboratory, Stanford University (revised July 1998). I. Bongartz, A. R. Conn, N. I. M. Gould, M. A. Saunders and Ph. L. Toint, A numerical comparison between the LANCELOT and MINOS packages for large-scale constrained optimization, Report SOL 97-6, Dept of EESOR, Stanford University (1997), 19 pages. I. Bongartz, A. R. Conn, N. I. M. Gould, M. A. Saunders and Ph. L. Toint, A numerical comparison between the LANCELOT and MINOS packages for large-scale constrained optimization: the complete results, Report SOL 97-7, Dept of EESOR, Stanford University (1997), 50 pages. |