PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Interactive multi-objective optimization for simulated moving bed processes

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, efficient optimization techniques are used to solve multi-objective optimization problems arising from Simulated Moving Bed (8MB) processes. SMBs are widely used in many industrial separations of chemical products and they are very challenging from the optimization point of view. With the help of interactive multi-objective optimization, several conflicting objectives can be considered simultaneously without making unnecessary simplifications, as it has been done in previous studies. The optimization techniques used are the interactive NIMBUS™ method and the IPOPT optimizer. To demonstrate the usefulness of these techniques, the results of solving an 8MB optimization problem with four objectives are reported.
Rocznik
Strony
283--302
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
autor
autor
autor
  • Dept. of Mathematical Information Technology P.O. Box 35 (Agora), FI-40014 University of Jyväskylä, Finland, jussi.hakanen@mit.jyu.fi
Bibliografia
  • BUCHANAN, J.T. (1997) A Naive Approach for Solving MCDM Problems: the GUESS Method. Journal of the Operational Research Society 48, 202-206.
  • DUNNEBIER, G., FRICKE, J. and KLATT, K.-U. (2000) Optimal Design and Operation of Simulated Moving Bed Chromatographic Reactors. Industrial & Engineering Chemistry Research 39, 2290-2304.
  • GILL, P.E., MURRAY, W. and WRIGHT, M.H. (1981) Practical Optimization. Academic Press Inc., London.
  • HAKANEN, J., HAKALA, J. and MANNINEN, J. (2006) An Integrated Multi-objective Design Tool for Process Design. Applied Thermal Engineering 26, 1393-1399.
  • HAKANEN, J., MIETTINEN, K., MAKELA, M.M. and MANNINEN, J. (2005) On Interactive Multiobjective Optimization with NIMBUS in Chemical Process Design. Journal of Multicriteria Decision Analysis 13, 125-134.
  • HASHIMOTO, K., ADACHI, S., NOUJIMA, H. and MARUYAMA, H. (1983) Models for the Separation of Glucose/Fructose Mixture Using a Simulated Moving Bed Adsorber. Journal of Chemical Engineering of Japan 16(5), 400-406.
  • KARLSSON, S. (2001) Optimization of a Sequential-Simulated Moving-Bed Separation Process with Mathematical Programming Methods. PhD thesis, Abo Akademi University, Abo. Finland.
  • KAWAJIRI, Y. and BIEGLER, L.T. (2006a) A Nonlinear Programming Superstructure for Optimal Dynamic Operations of Simulated Moving Bed Processes. Industrial & Engineering Chemistry Research 45, 8503-8513.
  • KAWAJIRI, Y. and BIEGLER, L.T. (2006b) Optimization Strategies for Simulated Moving Bed and Powerfeed Processes. AIChE J. 52(4), 1343-1350.
  • KO, D. and MOON, I. (2002) Multiobjective Optimization of Cyclic Adsorption Processes. Industrial & Engineering Chemistry Research 41(1), 93-104.
  • MIETTINEN, K. (1999) Nonlinear Multiobjective Optimization. Kluwer Academic Publishers, Boston.
  • MIETTINEN, K. and MAKELA, M.M. (1995) Interactive Bundle-Based Method for Nondifferentiable Multiobjective Optimization: NIMBUS. Optimization 34, 231-246.
  • MIETTINEN, K. and MAKELA, M.M. (2002) On Scalarizing Functions in Multiobjective Optimization. OR Spectrum 24, 193-213.
  • MIETTINEN, K. and MAKELA, M.M. (2006) Synchronous Approach in Interactive Multiobjective Optimization. European Journal of Operational Research 170, 909-922.
  • NAKAYAMA, H. (1995) Aspiration Level Approach to Interactive Multi-Objective Programming and Its Applications. In: P.M. Pardalos, Y. Siskos, and C. Zopounidis, eds., Advances in Multicriteria Analysis, 147-174. Kluwer Academic Publishers.
  • RUTHVEN, D.M. and CHING, C.B. (1989) Counter-current and Simulated Counter-current Adsorption Separation Processes. Chemical Engineering Science 44, 1011-1038.
  • SUBMARANI, H., HIDAJAT, K. and RAY, A. (2003) Optimization of Reactive 8MB and Varicol Systems. Computers & Chemical Engineering 27, 1883-1901.
  • TOUMI, A., HANISCH, F., and ENGELL, S. (2002) Optimal Operation of Continuous Chromatographic Processes: Mathematical Optimization of the VARICOL Process. Industrial and Engineering Chemistry Research 41, 4328-4337.
  • WACHTER, A. and BIEGLER, L.T. (2006) On the Implementation of an Interior-Point Filter Line-Search Algorithm for Large-Scale Nonlinear Programming. Mathematical Programming 106, 25-57.
  • WIERZBICKI, A.P. (1982) A Mathematical Basis for Satisficing Decision Making. Mathematical Modelling 3(25), 391-405.
  • WIERZBICKI, A.P. (1999) Reference Point Approaches. In: T. Gal, T.J. Stewart, and T. Hanne, eds., Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications, 9.1-9.39, Kluwer Academic Publishers, Boston.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0017-0040
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.