Constrained Optimization Algorithm

A Constrained Optimization Algorithm is an optimization algorithm that can be applied by an constrained optimization system (to solve a constrained optimization task).

• Example(s):
  • a Lagrangian Method, such as ADMM.
  • a Penalty Method.
  • an Interior Point Method.
• See: Vector Space, Constraint Rule, Unconstrained Optimization Algorithm, Geometric Optimality Conditions, Fritz John Conditions, Karush–Kuhn–Tucker Conditions, Linear Programming, Simplex Method, Polynomial Time, Quadratic Programming, Ellipsoid Method, Convex Function.

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References

2015

• (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/constrained_optimization#Solution_methods Retrieved:2015-11-8.
  • Many unconstrained optimization algorithms can be adapted to the constrained case, often via the use of a penalty method. However, search steps taken by the unconstrained method may be unacceptable for the constrained problem, leading to a lack of convergence. This is referred to as the Maratos effect.

1997

• (Luenberger, 1997) ⇒ David G. Luenberger. (1997). “Optimization by Vector Space Methods." Wiley Professional. ISBN:047118117X

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