Korbinian Krämer, Sven Kossack, Wolfgang Marquardt:
An efficient solution method for the MINLP optimization of chemical processes
In: V. Plesu, P.S. Agachi (Eds.): ESCAPE 17 (European Symposium On Computer Aided Process Engineering), Bucharest, Romania, 105-110
Process synthesis often involves the solution of large nonlinear discrete-continuous optimization problems, which are usually formulated as mixed-integer nonlinear programming (MINLP) or generalized disjunctive programming (GDP) problems and solved with MINLP solvers. This paper presents an efficient solution method for these problems named successive relaxed MINLP (SR-MINLP), where the model formulations are reformulated to contain only continuous variables. The discrete decisions are relaxed and successively tightened in a sequential solution procedure to facilitate convergence and to obtain local optima of good quality. The solution method is illustrated by a simple numerical example as well as a large and complex example from process synthesis.
MINLP, continuous reformulation, distillation design