Premium
Infeasible path optimization with sequential modular simulators
Author(s) -
Biegler L. T.,
Hughes R. R.
Publication year - 1982
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690280615
Subject(s) - modular design , block (permutation group theory) , mathematical optimization , path (computing) , convergence (economics) , computer science , process (computing) , nonlinear programming , quadratic programming , simple (philosophy) , algorithm , nonlinear system , mathematics , philosophy , physics , geometry , epistemology , quantum mechanics , economics , economic growth , operating system , programming language
Infeasible path optimization algorithms have been effective with equation‐solving or simultaneous modular process simulators. Using these simulators, successive quadratic programming is applied to large nonlinear programs. However, the algorithms are not directly applicable to commercial simulators of the sequential modular type. Here an infeasible path algorithm is presented which can easily be integrated with most commercial process simulators. The optimization problem remains small (10 or 20 variables) and the user merely replaces the convergence block with an “optimization” block. A simple process example demonstrates the operation, effectiveness, and potential of this algorithm.