Name
Abstract | ||
|---|---|---|
We develop an affine-scaling algorithm for box-constrained optimization which has the property that each iterate is a scaled cyclic Barzilai–Borwein (CBB) gradient iterate that lies in the interior of the feasible set. Global convergence is established for a nonmonotone line search, while there is local R-linear convergence at a nondegenerate local minimizer where the second-order sufficient optimality conditions are satisfied. Numerical experiments show that the convergence speed is insensitive to problem conditioning. The algorithm is particularly well suited for image restoration problems which arise in positron emission tomography where the cost function can be infinite on the boundary of the feasible set. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10107-007-0199-0 | Math. Program. |
Keywords | Field | DocType |
affine-scaling algorithm,convergence speed,nondegenerate local minimizer,feasible set,gradient iterate,global convergence,interior-point · affine-scaling · cyclic barzilai-borwein methods · cbb · pet · image reconstruction · global convergence · local convergence,affine-scaling interior-point cbb method,local r-linear convergence,cost function,box-constrained optimization,cyclic barzilai,satisfiability,linear convergence,second order,interior point,image restoration,local convergence,constrained optimization | Convergence (routing),Affine transformation,Mathematical optimization,Nonlinear programming,Feasible region,Line search,Local convergence,Interior point method,Mathematics,Constrained optimization | Journal |
Volume | Issue | ISSN |
119 | 1 | 1436-4646 |
Citations | PageRank | References |
20 | 1.03 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| William W. Hager | 1 | 1603 | 214.67 |
| Bernard A. Mair | 2 | 32 | 6.74 |
| Hongchao Zhang | 3 | 809 | 43.29 |