Name
Abstract | ||
|---|---|---|
In this paper we developed a general primal-dual nonlinear rescaling method with dynamic scaling parameter update (PDNRD) for convex optimization. We proved the global convergence, established 1.5-Q-superlinear rate of convergence under the standard second order optimality conditions. The PDNRD was numerically implemented and tested on a number of nonlinear problems from COPS and CUTE sets. We present numerical results, which strongly corroborate the theory. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/s10107-005-0603-6 | Math. Program. |
Keywords | Field | DocType |
primal-dual nonlinear,order optimality condition,convex optimization,global convergence,lagrangian,numerical result,primal-dual,nonlinear rescaling,nonlinear problem,duality,dynamic scaling parameter update,general primal-dual nonlinear,multipliers method,non linear programming,multiplier,convex programming,mathematical programming,rate of convergence | Convergence (routing),Mathematical optimization,Nonlinear system,Nonlinear programming,Dynamic scaling,Multiplier (economics),Duality (optimization),Rate of convergence,Convex optimization,Mathematics | Journal |
Volume | Issue | ISSN |
106 | 2 | 1436-4646 |
Citations | PageRank | References |
23 | 1.07 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Griva | 1 | 44 | 5.13 |
| Roman A. Polyak | 2 | 211 | 52.70 |