Interval Constraints with Learning: Application to Air Traffic Control

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9892)

Abstract

Lazy Clause Generation (LCG) is a learning extension of Constraint Programming that combines the power of SAT and CP. In this paper we present an extension of Lazy Clause Generation from finite domain constraints to interval constraints, that is: non-linear constraints over the reals. Because LCG solvers must be able to negate literals involved in computation, LCG for intervals must represent both open and closed intervals. This makes LCG for intervals quite different from LCG for integers. We illustrate the advantage of the technology by solving a mixed integer non-linear Air Traffic Control problem .

Keywords

Constraint Satisfaction Problem Boolean Variable Interval Arithmetic Interval Constraint Atomic Constraint 
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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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Data61, CSIROMelbourneAustralia
  2. 2.Department of Computing and Information SystemsUniversity of MelbourneMelbourneAustralia

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