Nonlinear constrained optimizer and parallel processing for golden block line search

Duc T. Nguyen, Wilson H. Tang, Yeou-Koung Tung, Hakizumwami B. Runesha

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

Generalized exponential penalty functions are constructed for the multiplier methods in solving nonlinear programming problems. The non-smooth extreme constraint Gext is replaced by a single smooth constraint Gs by using the generalized exponential function (base a>1). The well-known K.S. function is found to be a special case of our proposed formulation. Parallel processing for Golden block line search algorithm is then summarized, which can also be integrated into our formulation. Both small and large-scale nonlinear programming problems (up to 2000 variables and 2000 nonlinear constraints) have been solved to validate the proposed algorithms.

Original languageEnglish
Pages (from-to)469-477
Number of pages9
JournalComputer Assisted Mechanics and Engineering Sciences
Volume6
Issue number3
StatePublished - 1 Dec 1999
Event8th International Conference on Numerical Mathematics and Computational Mechanics (NMCM98) - Miskolc, Hung
Duration: 24 Aug 199827 Aug 1998

Fingerprint Dive into the research topics of 'Nonlinear constrained optimizer and parallel processing for golden block line search'. Together they form a unique fingerprint.

  • Cite this