• New set of functions for classes of convex optimization.
  • Enhanced support for linear optimization. »
  • Support for linear fractional optimization. »
  • Support for quadratic optimization. »
  • Support for second-order cone optimization. »
  • Support for semidefinite optimization. »
  • Support for conic optimization. »
  • Support for primal and dual solution properties.
  • Support for matrix- or formula-based modeling input.
  • Vector inequalities for modeling with vector-valued variables.
  • Automatic dimensional inference for vector-valued variables.
  • Automatic detection of convex problems in existing general optimization functions.
  • Automatic use of convex optimization for specific tasks.

Related Examples

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