Sequential Convex Programming Methods for Solving Nonlinear Optimization Problems with DC constraints

This paper investigates the relation between sequential convex programming (SCP) as, e.g., defined in [24] and DC (difference of two convex functions) programming. We first present an SCP algorithm for solving nonlinear optimization problems with DC constraints and prove its convergence. Then we combine the proposed algorithm with a relaxation technique to handle inconsistent linearizations. Numerical tests are performed to investigate the behaviour of the class of algorithms.Comment: 18 pages, 1 figur

The Summarized Evaluation of The US and Latin America Corporate Governance Standards After Financial Crisis, Corporate Scandals and Manipulation

There are many analytical papers and researches done in the field of examining and analyzing consequences of the Sarbanes Oxley Act (2002) and some done in the corporate governance in some Latin American countries. This paper chooses a different approach. First, it selects The US, Brazil and Chile, which represents for Latin American countries, as three (3) American countries to analyze their best suitable policies and corporate governance practices, in consideration of factors after crisis and scandals. Second, it aims to build a selected comparative set of standards for corporate governance system in the US and representative Latin American countries. Last but not least, this paper illustrates corporate governance standards that it might give proper recommendations to relevant governments and institutions in re-evaluating their current ones.corporate governance standards, board structure, code of best practice, financial crisis, corporate scandals, market manipulation, internal audit

A Primal-Dual Algorithmic Framework for Constrained Convex Minimization

We present a primal-dual algorithmic framework to obtain approximate solutions to a prototypical constrained convex optimization problem, and rigorously characterize how common structural assumptions affect the numerical efficiency. Our main analysis technique provides a fresh perspective on Nesterov's excessive gap technique in a structured fashion and unifies it with smoothing and primal-dual methods. For instance, through the choices of a dual smoothing strategy and a center point, our framework subsumes decomposition algorithms, augmented Lagrangian as well as the alternating direction method-of-multipliers methods as its special cases, and provides optimal convergence rates on the primal objective residual as well as the primal feasibility gap of the iterates for all.Comment: This paper consists of 54 pages with 7 tables and 12 figure