Trust regions based on conic functions in linear and nonlinear programming

An optimization method is developed based on ellipsoidal trust regions that are defined by conic functions. It provides a powerful unifying theory from which can be derived a variety of interesting and potentially useful optimization algorithms, in particular, conjugate‐gradient‐like algorithms for nonlinear minimization and Karmarkar‐like interior‐point algorithms for linear programming.