Singularity theory for nonlinear optimization problems

摘要

Techniques from the theory of singularities of smooth mappings are employed to study the reduction of nonlinear optimization problems to simpler forms. It is shown how singularity theory ideas can be used to: (1) reduce the decision-space dimensionality; (2) transform the constraint space to simpler form for primal algorithms; (3) provide sensitivity analysis.