Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations

Chemical Engineering Science

Volumn 62, Issue 9, 2007, Pages 2346-2365

  Agrawal, Naveen ^a   Rangaiah, G P ^a   Ray, Ajay K ^b   Gupta, Santosh K ^c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b UNIVERSITY OF WESTERN ONTARIO   (Canada)

^c INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Constrained dominance principle; Genetic algorithm; High pressure polyethylene reactor; Jumping gene; Multi objective optimization

Indexed keywords

BINARY CODES; CONSTRAINT THEORY; GENETIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; POLYETHYLENES; SET THEORY;

CONSTRAINED-DOMINANCE PRINCIPLE; HIGH-PRESSURE POLYETHYLENE REACTOR; JUMPING GENE;

CHEMICAL REACTORS;

BINARY CODES; CHEMICAL REACTORS; CONSTRAINT THEORY; GENETIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; POLYETHYLENES; SET THEORY;

EID: 33947705122     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2007.01.030     Document Type: Article

References (32)

1. Agrawal N., Rangaiah G.P., Ray A.K., and Gupta S.K. Multi-objective optimization of the operation of an industrial low-density polyethylene tubular reactor using genetic algorithm and its jumping gene adaptations. Industrial and Engineering Chemical Research 45 (2006) 3182-3199
2. Asteasuain M., Tonelli S.M., Brandolin A., and Bandoni J.A. Dynamic simulation and optimization of tubular polymerization reactors in gPROMS. Computers and Chemical Engineering 25 (2001) 509-515
3. Asteasuain M., Bandoni A., Sarmoria C., and Brandolin A. Simultaneous process and control system design for grade transition in styrene polymerization. Chemical Engineering Science 61 (2006) 3362-3378
4. Bhat, S.A., Gupta, S.K., 2006. Multi-objective optimization of an industrial semi-batch nylon-6 reactor using a new jumping gene adaptation of genetic algorithm, in preparation.
5. Brandolin, A., Capiati, N.J., Farber, J.N., Valles, E.M., 1988. Mathematical model for high-pressure tubular reactor for ethylene polymerization. Industrial and Engineering Chemical Research 27, 784-790.
6. Brandolin A., Valles E.M., and Farber J.N. High-pressure tubular reactors for ethylene polymerization optimization aspects. Polymer Engineering Science 31 (1991) 381-390
7. Brandolin A., Lacunza M.H., Ugrin P.E., and Capiati N.J. High-pressure polymerization of ethylene. An improved mathematical model for industrial tubular reactors. Polymer Reaction Engineering 4 (1996) 193-241
8. Cervantes A., Tonelli S., Brandolin A., Bandoni A., and Beigler L. Large-scale dynamic optimization of a low density polyethylene plant. Computers and Chemical Engineering 24 (2000) 983-989
9. Coulson, J.M., Richardson, J.F., Backhurst, J.R., Harker, J.H., 1996. Coulson & Richardson's Chemical Engineering: Fluid Flow, Heat Transfer and Mass Transfer, vol. I, fifth ed. Butterworth-Heinemann, Oxford, UK.
10. Deb K. An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering 186 (2000) 311-338
11. Deb K. Multiobjective Optimization Using Evolutionary Algorithms (2001), Wiley, Chichester, UK
12. Deb K., Pratap A., Agarwal A., and Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6 (2002) 182-197
13. Ehrlich P., and Mortimer G.A. Fundamentals of the free radical polymerization of ethylene. Advance Polymer Science 7 (1970) 386-448
14. Goto S., Yamamoto K., Furui S., and Sugimoto M. Computer model for commercial high-pressure polyethylene reactor based on elementary reaction rates obtained experimentally. Journal of Applied Polymer Science 36 (1981) 21-40
15. Gupta S.K., Kumar A., and Krishnamurthy M.V.G. Simulation of tubular low-density polyethylene. Polymer Engineering Science 25 (1985) 37-47
16. Guria C., Bhattacharya P.K., and Gupta S.K. Multi-objective optimization of reverse osmosis desalination units using different adaptations of the non-dominated genetic algorithm (NSGA). Computers and Chemical Engineering 29 (2005) 1977-1995
17. Kalyon D.M., Chiou Y.N., Kovenklioglu S., and Bouaffar A. High pressure polymerization of ethylene and rheological behavior of polyethylene product. Polymer Engineering Science 33 (1994) 804-814
18. Kasat R.B., and Gupta S.K. Multi-objective optimization of an industrial fluidized bed catalytic cracking unit (FCCU) using genetic algorithm with the jumping genes operator. Computers and Chemical Engineering 27 (2003) 1785-1800
19. Kiparissides C., Verros G., and MacGregor J.F. Mathematical modeling, optimization, and quality control of high pressure ethylene polymerization reactors. Journal of Macromolecular Science-Reviews in Macromolecular Chemistry and Physics C33 (1993) 437-527
20. Kiparissides C., Verros G., and Pertsinidis A. On-line optimization of a high-pressure low-density polyethylene tubular reactor. Chemical Engineering Science 49 (1994) 5011-5024
21. Kondratiev J.N., and Ivanchev S.S. Possibilities for optimization of technological modes for ethylene polymerization in autoclave and tubular reactors. Chemical Engineering Journal 107 (2005) 221-226
22. Luft G., Kampf R., and Seidl H. Synthesis conditions and structure of low density polyethylene i. short and long chain branching. Die Angewandte Makromolekulare Chemie 108 (1982) 203-217
23. Machi S., Kawakami W., Yamaguchi K., Hosaki Y., Hagiwara M., and Sugo T. Structure and properties of polyethylene produced by γ-radiation polymerization in flow system. Journal of Applied Polymer Science 12 (1968) 2639-2647
24. Man, K.F., Chan, T.M., Tang, K.S., Kwong, S., 2004. Jumping genes in evolutionary computing. Proceedings of the Thirtieth Annual Conference of the IEEE Industrial Electronics Society (IECON), Busan, Korea; 2-6 November 2004, vol. 2, IEEE, Piscataway, NJ, p. 1268.
25. Mavridis H., and Kiparissides C. Optimization of a high-pressure polyethylene tubular reactor. Polymer Process Engineering 3 (1985) 263-290
26. Padhiyar N., Bhartiya S., and Gudi R.D. Optimal grade transition in polymerization reactors: a comparative case study. Industrial and Engineering Chemical Research 45 (2006) 3583-3592
27. Simoes A., and Costas E. Transposition: a biologically inspired mechanism to use with genetic algorithm. In: Dobnikar A., Steele N., and Pearson D. (Eds). Proceedings of the Fourth International Conference on Neural Networks and Genetic Algorithms (ICANNGA99) (1999), Springer, Portoroz Slovenia 178
28. Tarafder A., Rangaiah G.P., and Ray A.K. Multiobjective optimization of an Industrial styrene monomer manufacturing process. Chemical Engineering Science 60 (2005) 347-363
29. Tarafder A., Lee B.C.S., Ray A.K., and Rangaiah G.P. Multiobjective optimization of an industrial ethylene reactor using nondominated sorting genetic algorithm. Industrial and Engineering Chemical Research 44 (2006) 124-141
30. Yao F.Z., Lohi A., Upreti S.R., and Dhib R. Modeling, simulation and optimal control of ethylene polymerization in non-isothermal, high-pressure tubular reactors. International Journal of Chemical Reactor Engineering 2 (2004) 1-25
31. Yoon B.J., and Rhee H.K. A study of the high-pressure polyethylene tubular reactor. Chemical Engineering Communication 24 (1985) 253-256
32. Zabisky R.C.M., Chan W.M., Gloor P.E., and Hamielec A.E. A kinetic model for olefin polymerization in high-pressure tubular reactors: a review and update. Polymer 33 (1992) 2243-2261