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A Stochastic Algorithm for Finding Points Satisfying Infinitely Many Inequality Constraints

  • Y. Wardi
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 83)

Abstract

An optimization algorithm for finding a point satisfying infinitely many inequality constraints is presented. The algorithm approximates the maximum of an infinite number of inequalities at a point by performing a set of random experiments, resulting in a finite number of inequalities, over which the maximum is taken. It uses a constraint-dropping scheme, by which it eliminates points from a constraint-set at hand, which are felt to be irrelevant. At each point the algorithm constructs, it evaluates a measure of optimality, which indicates how close the point is to satisfying all of the constraints. It uses this measure to determine the number of random experiments performed. The number of such experiments tends to be small initially, when the point at hand is far from satisfying all of the constraints, and it increases gradually as a solution point is approached.

Keywords

Infinite Number Inequality Constraint Accumulation Point Solution Point Algorithm Construct 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer Science+Business Media Dordrecht 1986

Authors and Affiliations

  • Y. Wardi
    • 1
  1. 1.School of Electrical EngineeringGeorgia Institute of TechnologyAtlantaUSA

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