This paper presents a trust-region algorithm for n-dimensional nonlinear optimization subject to m nonlinear inequality constraints. Equivalent KKT conditions are derived, being the basis for constructing the new algorithm. Global convergence of the algorithm to a first-order KKT point is established under mild conditions on the trial steps. Condition $m\leq n$ is required.
"Global convergence of a trust-region algorithm for inequality constrained optimization." Hokkaido Math. J. 30 (1) 113 - 136, February 2001. https://doi.org/10.14492/hokmj/1350911927