Abstract. A second scheme for the sagitta method is presented. This method uses a “global ” viewpoint of the linear problem, and, in this feasible-point version, it also takes advantage of the additional “local” information that a feasible point supplies. The computational results obtained

framework in which the moving-average root is local to −1 to document how the MIC performs better in selecting appropriate values of k. In monte-carlo experiments, the MIC is found to yield huge size improvements to the DF GLS and the feasible point optimal PT test developed in Elliott, Rothenberg and Stock

Various algorithms can compute approximate feasible points or approximate solutions to equality and bound constrained optimization problems. In exhaustive search algorithms for global optimizers and other contexts, it is of interest to construct bounds around such approximate feasible points

-convex part and solve the resulting convex problem. However, these techniques are seldom successful in even obtaining a feasible solution when the QCQP matrices are indefinite. In this letter, a new feasible point pursuit successive convex approximation (FPP-SCA) algo-rithm is proposed for non-convex QCQPs

In this work we define a trust-region feasible-point algorithm for approximating solutions of the nonlinear system of equalities and inequalities F(x, y) = 0, y ≥ 0, where F: R^n × R^m → R^p is continuously differentiable. This formulation is quite general; the Karush

, a small region must be constructed within which existence of a feasible point can be proven, and an upper bound on the objective over that region is obtained. We had previously proposed a perturbation technique for constructing such a region. In this work, we propose a much simplified and improved

be estimated by ML. Furthermore, ML provides an uncertainty of the estimated parameters what may be used to decide if point estimates are sufficiently accurate or if interval estimation (giving a region of suitable parameters) is more adequate. We discuss various practical and theoretical problems with MLE

informs ® doi 10.1287/ijoc.1030.0046 © 2004 INFORMS This paper develops a method for moving quickly and cheaply from an arbitrary initial point at an extreme distance from the feasible region to a point that is relatively near the feasible region of a nonlinearly constrained model. The method is a

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Attempts to generalize the Internet's point-to-point communication abstraction to provide services like multicast, anycast, and mobility have faced challenging technical problems and deployment barriers. To ease the deployment of such services, this paper proposes an overlay-based Internet