Titlebook: Global Optimization and Constraint Satisfaction; First International Christian Bliek,Christophe Jermann,Arnold Neumaier Conference proceed

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Consistency Techniques for the Localization of a Satelliteem over continuous domains with a large number (several thousands) of variables and constraints. Consistency techniques are then shown to be particularly efficient to contract the domains for the variables involved. This is probably due to the large number of redundancies naturally involved in the c

homeostasis

Computing Interval Parameter Bounds from Fallible Measurements Using Overdetermined (Tall) Systems o systems, there are more interval equations than unknowns. As a result, these systems can appear to be inconsistent when they are not. An algorithm is given to compute interval nonlinear parameter bounds from fallible data and to possibly prove that no bounds exist because the tall system is inconsi

overwrought

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Numerical Constraint Satisfaction Problems with Non-isolated Solutionser, most of the working systems are designed to deliver . solutions with an arbitrary accuracy. This works generally well for systems with isolated solutions but less well when there is a . (e.g. under-constrained problems, problems with inequalities). In many practical applications, such large sets

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Jennie P. Mather,Penelope E. Robertssolutions to unconstrained and constrained global optimization problems. After briefly reviewing some of these techniques and GlobSol’s development history, we provide the first overall description of GlobSol’s algorithm. Giving advice on use, we point out strengths and weaknesses in GlobSol’s appro

Aids209

Takashi Kurahashi,Geoffrey H. Goldnvex relaxation which is used for generating solution candidates and computing lower bounds of the optimal value. The relaxation is generated by reformulating the given MINLP as a block-separable problem, and replacing nonconvex functions by convex underestimators. Results on medium size MINLPs are

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