Erratum: Computational studies using a novel simplical-approximation based algorithm for MINLP optimization (Computers and Chemical Engineering (2004) 28 (1771-1780) DOI: 10.1016/j.compchemeng.2004.02.029);Computational studies using a novel simplicial-approximation based algorithm for MINLP optimization

Computers and Chemical Engineering

Volumn 28, Issue 9, 2004, Pages 1771-1780

  Goyal, Vishal ^a   Ierapetritou, Marianthi G ^a  

^a The State University of New Jersey   (United States)

Author keywords

Decomposition algorithm; MINLP optimization; Simplicial approximation

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL METHODS; NONLINEAR PROGRAMMING; PROBLEM SOLVING;

DECOMPOSITION ALGORITHMS; MIXED INTEGER NONLINEAR PROGRAMMING (MINP);

CHEMICAL ENGINEERING;

COMPUTER;

ALGORITHM; ARTICLE; COMPUTER PROGRAM; DECOMPOSITION; FEASIBILITY STUDY; MATHEMATICAL ANALYSIS; STATISTICAL MODEL; STRUCTURE ANALYSIS;

EID: 2442519248     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2004.10.006     Document Type: Erratum

References (19)

1. Adjiman, C. S., Schweiger, C. A., & Floudas, C. A. (1998). Mixed integer nonlinear optimization in process synthesis. In D.-Z. Du & P. M. Pardalos (Eds.), Handbook of Combinatorial Optimization. Kluwer Academic.
2. Brooke, A., Kendrick, D., & Meeraus, A. (1988). GAMS: A user's guide. The Scientific Press.
3. Duran M.A., Grossmann I.E. An outer approximation method for a class of mixed-integer nonlinear programs. Mathmetical Programming. 36:1986;307-339
4. Eggleston, H. G. (1966). Convexity. Cambridge University Press.
5. Fletcher R., Leyffer S. Solving mixed-integer nonlinear programs by outer approximation. Mathmetical Programming. 66:1994;327
6. Geoffrion A.M. Generalized benders decomposition. Journal of Optimization Theory. 10:1972;237-262
7. Goyal V., Ierapetritou M.G. Determination of operability limits using simplicial approximation. AIChE Journal. 48:2002;2902
8. Goyal V., Ierapetritou M.G. A framework for evaluating the feasibility/operability of non-convex processes. AIChE Journal. 49:2003a;1233
9. Goyal V., & Ierapetritou M. G. (2003b). MINLP optimization using simplicial approximation method for classes of nonconvex problems. Frontiers in Global Optimization. (pp. 165-196). Kluwer Academic Publishers.
10. Harjunkoski I., Westerlund T., Pörn R., Skrifvars H. Different transformations for solving non-convex trim-loss problems by MINLP. European Journal of Operational Research. 105:1998;594-603
11. Kelly J.E. The cutting plane method for solving convex programs. Journal of SIAM. 8:1960;703
12. Kocis G.R., Grossmann I.E. Relaxation strategy for the structural optimization of process flow-sheets. Industrial and Engineering Chemical Research. 26:1987;1869
13. Kocis G.R., Grossmann I.E. Global optimization of nonconvex MINLP problems in process synthesis. Industrial and Engineering Chemical Research. 27:1988;1407
14. Leyffer S. (2003). MacMINLP: AMPL collection of MINLP Test Problems. http://www-unix.mcs.anl.gov/∼leyffer/MacMINLP/.
15. Murtagh, B. A., & Saunders, M. A. (1998). MINOS 5.5 user's guide, report SOL 83-20R. Department of OR, Stanford University.
16. Nemhauser G. L., & Wolsey L. A. (1988). Integer and combinatorial optimization. Wiley/Interscience.
17. Viswanathan J., Grossmann I.E. A combined penalty function and outer approximation method for MINLP optimization. Computation and Chemical Engineering. 14:1990;769
18. Westerlund T., Petterson F. An extended cutting plane method for solving convex MINLP problems. Computation and Chemical Engineering Supplement. 19:1995;131
19. Zhang, Y., & Gao, L. (2001). On numerical solution of the maximum volume ellipsoid problem, CAAM technical report TR01-15. Rice University.