new exact penalty functions for nonlinear constrained optimization problems
Clicks: 77
ID: 194029
2014
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
22.8
/100
77 views
4 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #316 of 631 articles by views in science and technology of advanced materials
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 631 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.
| Reference Key |
liu2014abstractnew
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Bingzhuang Liu;Wenling Zhao |
| Journal | science and technology of advanced materials |
| Year | 2014 |
| DOI |
10.1155/2014/738926
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.