Editing Active-set method (section)

== Performance ==
Consider the problem of Linearly Constrained Convex Quadratic Programming. Under reasonable assumptions (the problem is feasible, the system of constraints is regular at every point, and the quadratic objective is strongly convex),  the active-set method terminates after finitely many steps, and yields a global solution to the problem. Theoretically, the active-set method may perform a number of iterations exponential in ''m'', like the [[simplex method]]. However, its practical behaviour is typically much better.<ref name=":0">{{Cite web |last=Nemirovsky and Ben-Tal |date=2023 |title=Optimization III: Convex Optimization |url=http://www2.isye.gatech.edu/~nemirovs/OPTIIILN2023Spring.pdf}}</ref>{{Rp|location=Sec.9.1}}