Nous pr esentons un algorithme parall ele d eterministe pour la r esolution d'un syst eme d' equations lin eaires Ax = b sur un corps de caract eristique nulle. Cet algorithme s'ex ecute en temps O(log 2 n) et utilise O(M(n)) processeurs arithm etiques si M(n) est le nombre de processeurs requis pour le produit de matrices en temps O(log n). Abstract. We present a deterministic parallel algorit...

In this paper, we investigate the transitional dynamics and quasi-periodic solution appearing after the Saddle-Node (SN) bifurcation of a periodic solution in an inductor-coupled asymmetrical van der Pol oscillators with hard-type nonlinearity. In particular, we elucidate, by investigating global bifurcation of unstable manifold (UM) of saddles, that transitional dynamics and quasi-periodic sol...

This paper concerns some practical issues associated with the formulation of sequential quadratic programming (SQP) methods for large-scale nonlinear optimization. SQP methods find an approximate solution of a sequence of quadratic programming (QP) subproblems in which a quadratic model of the objective function is minimized subject to the linearized constraints. Extensive numerical results are...

We present eecient algorithms for solving Legendre equations over Q (equivalently, for nding rational points on rational conics) and parametriz-ing all solutions. Unlike existing algorithms, no integer factorization is required , provided that the prime factors of the discriminant are known.

Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...

The goal of robust optimization problems is to find an optimal solution that is minimally sensitive to uncertain factors. Uncertain factors can include inputs to the problem such as parameters, decision variables, or both. Given any combination of possible uncertain factors, a solution is said to be robust if it is feasible and the variation in its objective function value is acceptable within ...