Outer Trust-Region Method for Constrained Optimization

Given an algorithm A for solving some mathematical problem based on the iterative solution of simpler subproblems, an outer trust-region (OTR) modification of A is the result of adding a trust-region constraint to each subproblem. The trust-region size is adaptively updated according to the behavior of crucial variables. The new subproblems should not be more complex than the original ones, and the convergence properties of the OTR algorithm should be the same as those of Algorithm A. In the present work, the OTR approach is exploited in connection with the ""greediness phenomenon"" of nonlinear programming. Convergence results for an OTR version of an augmented Lagrangian method for nonconvex constrained optimization are proved, and numerical experiments are presented.

Amylopectin-rich starch plasticized with glycerol for polymer electrolyte application

This paper describes the preparation and characterization of a solid polymer electrolyte based on amylopectin-rich starch plasticized with glycerol. The samples were characterized through ionic conductivity (sigma) measurements, scanning electron microscopy, thermal analysis, and spectroscopy in the UV-Vis-NIR region. The results showed that the highest sigma (1.1 x 10(-4) Scm(-1) at 30 degrees C) was obtained for the sample with n = [O]/[Li] = 6.5 ratio. In addition, the samples plasticized with 30-35 wt.% of glycerol presented high ionic conductivity, transparency and conduction stability. The ionic conductivity measurements as a function of lithium salt contents showed a maximum for n=6.5. The ionic conductivity as a function of time for amylopectin-rich starch plasticized with 30 wt.% of glycerol and containing [O]/[Li] = 10 showed conduction stability over 6 months (sigma similar to 3.01 x 10(-5) S cm(-1)). (C) 2010 Elsevier B.V. All rights reserved.