Newton's method for large bound-constrained optimization problems.

Journal Article · Fri Jan 01 00:00:00 EST 1999 · SIAM J. Optimization

DOI:https://doi.org/10.1137/S1052623498345075· OSTI ID:942618

Lin, C -J; More, J J

We analyze a trust region version of Newton's method for bound-constrained problems. Our approach relies on the geometry of the feasible set, not on the particular representation in terms of constraints. The convergence theory holds for linearly constrained problems and yields global and superlinear convergence without assuming either strict complementarity or linear independence of the active constraints. We also show that the convergence theory leads to an efficient implementation for large bound-constrained problems.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: DE-AC02-06CH11357
• OSTI ID: 942618
• Report Number(s): ANL/MCS/JA-33082; TRN: US200920%%76
• Journal Information: SIAM J. Optimization, Vol. 9, Issue 4 ; 1999; ISSN 1052-6234
• Country of Publication: United States
• Language: ENGLISH

Related Subjects

97 MATHEMATICS AND COMPUTING
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ALGORITHMS
CONVERGENCE
GEOMETRY
IMPLEMENTATION
LINEAR PROGRAMMING
NEWTON METHOD
OPTIMIZATION