All Areas Submissions - November 2003

Applications — Science and Engineering
Characterizing polynomials with roots in a semi-algebraic set
Jean B. Lasserre

Global Optimization
Local optima smoothing for global optimization
Bernardetta Addis, Marco Locatelli, Fabio Schoen

Applications — OR and Management Sciences
Two new proofs of Afriat's theorem
A. Fostel, H.E. Scarf, M.J. Todd

Linear, Cone and Semidefinite Programming
Sums of Squares Relaxations of Polynomial Semidefinite Programs
Masakazu Kojima

Nonlinear Optimization
Optimal Direct Determination of Sparse Jacobian Matrices
Shahadat Hossain, Trond Steihaug

Linear, Cone and Semidefinite Programming
On the optimal parameter of a self-concordant barrier over a symmetric cone
Domingos M. Cardoso, Luís A. Vieira

Linear, Cone and Semidefinite Programming
A Parallel Primal-Dual Interior-Point Method for Semidefinite Programs Using Positive Definite Matrix Completion
Kazuhide Nakata, Makoto Yamashita, Katsuki Fujisawa, Masakazu Kojima

Combinatorial Optimization
Computational Complexity, Fairness, and the Price of Anarchy of the Maximum Latency Problem
Jose R. Correa, Andreas S. Schulz, Nicolas E. Stier Moses

Nonlinear Optimization
An interior-point L1-penalty method for nonlinear optimization
N. I. M. Gould, D. Orban, Ph. L. Toint

Global Optimization
Fuzzy Control of Stochastic Global Optimization Algorithms and Very Fast Simulated Reannealing
Hime Aguiar e O. Jr.

Linear, Cone and Semidefinite Programming
Convergence of infeasible-interior-point methods for self-scaled conic programming
Bharath Kumar Rangarajan, Michael Todd

Applications — Science and Engineering
Quadratic interior-point methods in statistical disclosure control
Jordi Castro

Linear, Cone and Semidefinite Programming
An Adaptive Self-Regular Proximity Based Large-Update IPM for LO
Maziar Salahi, Tama's Terlaky

Applications — Science and Engineering
A New Computational Approach to Density Estimation with Semidefinite Programming
Tadayoshi Fushiki, Shingo Horiuchi, Takashi Tsuchiya

Applications — OR and Management Sciences
A Statistical Test for Comparing Success Rates
Eric Taillard