An affine scaling method for optimization problems with polyhedral constraints
Document Type
Article
Publication Date
1-1-2014
Abstract
Recently an affine scaling, interior point algorithm ASL was developed for box constrained optimization problems with a single linear constraint (Gonzalez-Lima et al.; SIAM J. Optim. 21:361-390, 2011). This note extends the algorithm to handle more general polyhedral constraints. With a line search, the resulting algorithm ASP maintains the global and R-linear convergence properties of ASL. In addition, it is shown that the unit step version of the algorithm (without line search) is locally R-linearly convergent at a nondegenerate local minimizer where the second-order sufficient optimality conditions hold. For a quadratic objective function, a sublinear convergence property is obtained without assuming either nondegeneracy or the second-order sufficient optimality conditions. © 2013 Springer Science+Business Media New York.
Publication Source (Journal or Book title)
Computational Optimization and Applications
First Page
163
Last Page
183
Recommended Citation
Hager, W., & Zhang, H. (2014). An affine scaling method for optimization problems with polyhedral constraints. Computational Optimization and Applications, 59 (1-2), 163-183. https://doi.org/10.1007/s10589-013-9535-x