Large-scale linearly constrained optimization | Zendy

B. A. Murtagh | Zendy; Michael A. Saunders | Zendy

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Large-scale linearly constrained optimization

Author(s) -

B. A. Murtagh,

Michael A. Saunders

Publication year - 1978

Publication title -

mathematical programming

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.358

H-Index - 131

eISSN - 1436-4646

pISSN - 0025-5610

DOI - 10.1007/bf01588950

Subject(s) - minos , variety (cybernetics) , mathematical optimization , mathematics , simplex algorithm , simplex , scale (ratio) , code (set theory) , algorithm , nonlinear system , numerical analysis , linear programming , sparse matrix , matrix (chemical analysis) , nonlinear programming , constrained optimization , computer science , combinatorics , statistics , physics , materials science , set (abstract data type) , quantum mechanics , nuclear physics , neutrino , composite material , gaussian , programming language , neutrino oscillation , mathematical analysis

An algorithm for solving large-scale nonlinear programs with linear constraints is presented. The method combines efficient sparse-matrix techniques as in the revised simplex method with stable quasi-Newton methods for handling the nonlinearities. A general-purpose production code (MINOS) is described, along with computational experience on a wide variety of problems.

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