Hong, W.R.W.R.HongTan, P.C.P.C.TanVu, Q.D.Q.D.VuLi, P.P.Li2022-03-112022-03-112009https://publica.fraunhofer.de/handle/publica/36501910.1016/S1570-7946(09)70262-7We present an improved quasi-sequential approach to large-scale dynamic process optimization. This new approach incorporates the quasi-sequential approach with the interior point method to handle inequality constraints. In this way the eventual optimization problem to be solved becomes a NLP without constraints. Mathematical derivations and computation schemes are developed. We first take a two-dimensional constrained optimization problem as an example; the result is compared with the simultaneous and quasi-sequential approach in terms of path solution with a graphical interpretation. A highly nonlinear reactor optimal control problem is also taken to demonstrate the effectiveness of this approach.en004670conference paper