Name
Abstract | ||
|---|---|---|
Many practical chemical engineering problems involve the determination of optimal trajectories given multiple and conflicting objectives. These conflicting objectives typically give rise to a set of Pareto optimal solutions. To enhance real-time decision making efficient approaches are required for determining the Pareto set in a fast and accurate way. Hereto, the current paper illustrates the use of the freely available toolkit ACADO Multi-Objective (www.acadotoolkit.org) on several chemical examples. The rationale behind ACADO Multi-Objective is the integration of direct optimal control methods with scalarisation-based multi-objective methods enabling the exploitation of fast deterministic gradient-based optimisation routines. (C) 2011 Elsevier Ltd. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.compchemeng.2011.11.002 | Computers & Chemical Engineering |
Keywords | Field | DocType |
Multi-objective optimisation,Dynamic optimisation,Optimal control,Open source,Pareto set | Chemical process,Mathematical optimization,Optimal control,Computer science,Pareto optimal,Pareto principle | Journal |
Volume | ISSN | Citations |
37 | 0098-1354 | 12 |
PageRank | References | Authors |
0.82 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Filip Logist | 1 | 64 | 10.75 |
| Mattia Vallerio | 2 | 26 | 2.62 |
| Boris Houska | 3 | 214 | 26.14 |
| Moritz Diehl | 4 | 1343 | 134.37 |
| Jan F. M. Van Impe | 5 | 58 | 11.27 |