Hidden Convexity in Partially Separable Optimization

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The paper identifies classes of nonconvex optimization problems whose convex relaxations have optimal solutions which at the same time are global optimal solutions of the original nonconvex problems. Such a hidden convexity property was so far limited to quadratically constrained quadratic problems with one or two constraints. We extend it here to problems with some partial separable structure. Among other things, the new hidden convexity results open up the possibility to solve multi-stage robust optimization problems using certain nonlinear decision rules.
Original languageEnglish
Place of PublicationTilburg
PublisherOperations research
Publication statusPublished - 2011

Publication series

NameCentER Discussion Paper


  • convex relaxation of nonconvex problems
  • hidden convexity
  • partially separable functions
  • robust optimization


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