5. Optimization-Based Approaches to Computational Molecular Design

  1. Prof. Efstratios N. Pistikopoulos2,
  2. Prof. Michael C. Georgiadis2,
  3. Dr. Vivek Dua3,
  4. Dr. Claire S. Adjiman2 and
  5. Dr. Amparo Galindo2
  1. J. C. Eslick,
  2. S. M. Shulda,
  3. P. Spencer and
  4. K. V. Camarda

Published Online: 27 JUN 2011

DOI: 10.1002/9783527631315.ch5

Process Systems Engineering: Molecular Systems Engineering, Volume 6

Process Systems Engineering: Molecular Systems Engineering, Volume 6

How to Cite

Eslick, J. C., Shulda, S. M., Spencer, P. and Camarda, K. V. (2011) Optimization-Based Approaches to Computational Molecular Design, in Process Systems Engineering: Molecular Systems Engineering, Volume 6 (eds E. N. Pistikopoulos, M. C. Georgiadis, V. Dua, C. S. Adjiman and A. Galindo), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany. doi: 10.1002/9783527631315.ch5

Editor Information

  1. 2

    Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, Roderic Hill Building, South Kensington Campus, London SW7 2AZ, UK

  2. 3

    Centre for Process Systems Engineering, Department of Chemical Engineering, University College London, London WC1E 7JE, UK

Author Information

  1. Kansas University, Chemical & Petroleum Engineering, Learned Hall, Room 4132E, 1530 West 15th Street, Lawrence, KS 66045-7609, USA

Publication History

  1. Published Online: 27 JUN 2011
  2. Published Print: 24 MAR 2011

ISBN Information

Print ISBN: 9783527316953

Online ISBN: 9783527631315

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Keywords:

  • computer-aided molecular design (CAMD);
  • mixed-integer nonlinear programs (MINLP);
  • quantitative structure–property relations (QSPR);
  • Tabu search (TS);
  • crosslink density (CD);
  • Tabu list;
  • molecular simulation

Summary

This chapter contains sections titled:

  • Introduction and Motivation

  • Quantitative Structure–Property Relationships

  • Problem Formulations for CAMD

  • Mathematical Techniques for the Solution of CAMD Optimization Problems

  • The Tabu Search Algorithm

  • Case Study

  • Conclusions and Future Directions