Solving Nonlinear Systems by Constraint Inversion and Interval Arithmetic

  • Authors:
  • Martine Ceberio;Laurent Granvilliers

  • Affiliations:
  • -;-

  • Venue:
  • AISC '00 Revised Papers from the International Conference on Artificial Intelligence and Symbolic Computation
  • Year:
  • 2000

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Abstract

A reliable symbolic-numeric algorithm for solving nonlinear systems over the reals is designed. The symbolic step generates a new system, where the formulas are different but the solutions are preserved, through partial factorizations of polynomial expressions and constraint inversion. The numeric step is a branch-and-prune algorithm based on interval constraint propagation to compute a set of outer approximations of the solutions. The processing of the inverted constraints by interval arithmetic provides a fast and efficient method to contract the variables' domains. A set of experiments for comparing several constraint solvers is reported.