Optimal solution of MINLP problems using modified genetic algorithm

Chemical Product and Process Modeling

Volumn 1, Issue 1, 2006, Pages

  Danish, Mohd ^a   Kumar, Surendra ^b   Qamareen, Arees ^a   Kumar, Shashi ^b  

^a ALIGARH MUSLIM UNIVERSITY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

Elitism; MINLP; Optimization; Real genetic algorithm

Indexed keywords

GENETIC ALGORITHMS; GLOBAL OPTIMIZATION; INTEGER PROGRAMMING; MATLAB; PARAMETER ESTIMATION; POLYNOMIALS; SCHEDULING;

BATCH PLANT DESIGN; ELITISM; REAL GENETIC ALGORITHMS;

INDUSTRIAL ENGINEERING;

EID: 35948932693     PISSN: 19342659     EISSN: None     Source Type: Journal    
DOI: 10.2202/1934-2659.1010     Document Type: Article

References (60)

1. Androulakis, LP., and Venkatasubramanian, V.A. (1991), Genetic algorithmic framework for process design and optimization, Computers and Chemical Engineering, 15(4), 217-228.
2. Angira, R., and Babu, B.V. (2006), Optimization of process synthesis and design problems: A modified differential evolution approach, Chemical Engineering Science, 61, 4707-4721.
3. Backhouse, P.G., Fotheringham, A.F., and Allan, G. (1997), A comparison of a genetic algorithm with an experimental design technique in the optimization of a production process, The Journal of the Operational Research Society, 48(3), 247-254.
4. Bernal-Haro, L., Azzaro-Pantel, C., Pibouleau, L., and Domenech, S. (2002a), Multiobjective batch plant design: A two-stage methodology, 1. Development of a design-oriented discrete-event simulation model, Ind. Eng. Chem. Res., 41, 5727-5742.
5. Bernal-Haro, L., Azzaro-Pantel, C., Pibouleau, L., and Domenech, S. (2002b), Multiobjective batch plant design: A two-stage methodology, 2. Development of a genetic algorithm and result analysis, Ind. Eng. Chem. Res., 41, 5743-5758.
6. Berning, G., Brandenburg, M., Gürsoy, K., Mehta, V., and Tolle, Franz-Josef (2002), An integrated system solution for supply chain optimization in the chemical process industry, OR Spectrum, 24, 371-401.
7. Biegler, L.T., Grossmann, I.E., and Westerberg, A.W. (1997), Systematic methods of chemical process design, New Jersey: Prentice Hall PTR.
8. Cardoso, M.F., Salcedo, R.L., de Azevedo, S.F., and Barbosa, D. (1997), A simulated annealing approach to the solution of MINLP problems, Computers and Chemical Engineering, 21(12), 1349-1364.
9. Cardoso, M.F., Salcedo, R.L., de Azevedo, S.F., and Barbosa, D. (2000), Optimization of reactive distillation processes with simulated annealing, Chemical Engineering Science, 55, 5059-5078.
10. Castell, C.M.L., Lakshmanan, R., Skilling, J.M., and Bañares- Alcántara, R. (1998), Optimization of process plant layout using genetic algorithms, Computers and Chemical Engineering, 22, Suppl., S993-S996.
11. Coello Coello, C.A., Van Veldhuizen, D.A., and Lamont, G.B. (2002), Evolutionary algorithms for solving multi-objective problems, New York, USA: Kluwer Academic/ Plenum Pub.
12. Costa, L., and Oliveira, P. (2001), Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems, Computers and Chemical Engineering, 25, 257-266.
13. Danish, M., Qamareen, A., Kumar, S., and Kumar, S. (2006), Letter to the Editor, Computers and Chemical Engineering (communicated).
14. Deb, K. (1995), Optimization for engineering design: algorithms and examples, New Delhi, India: Prentice Hall.
15. Deb, K. (1999b), An introduction to genetic algorithms, Sādhanā 24(4), 293-315.
16. Deb, K. (1999c), Multi-objective genetic algorithms: Problem difficulties and construction of test problems, Evolutionary Computation Journal, 7(3), 205-230.
17. Deb, K. (2000), An efficient constraints handling method for genetic algorithms, Computer Methods in Applied Mechanics and Engineering, 186(2-4), 311-338.
18. Deb, K., Agrawal, S., Pratap, A. and Meyarivan, T. (2000a), A fast and elitist multi-objective genetic algorithm: NSGA-II, Technical Report 200001, Indian Institute of Technology, Kanpur: Kanpur Genetic Algorithms Laboratory (KanGAL).
19. Deb, K., Agrawal, S., Pratap, A. and Meyarivan, T. (2000b), A fast and elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, In Proceedings of Parallel Problem Solving from Nature VI (PPSN-VI), pp. 849-858.
20. Deb, K. (2001), Multi-objective optimization using evolutionary algorithms, Chichester, England: John Wiley & Sons Ltd.
21. Dedieu, S., Pibouleau, L., Azzaro-Pantel, C., and Domenech, S. (2003), Design and retrofit of multiobjective batch plants via a multicriteria genetic algorithm, Computers and Chemical Engineering, 27, 1723-1740.
22. Dorigo, M., Maniezzo, V., and Colorni, A. (1996), The ant system: Optimization by a colony of cooperating agents, IEEE Transactions on Systems Man and Cybernatics B, 26(2), 29-41.
23. Dorigo, M., and Stützle, T. (2005), Ant colony optimization, New Delhi, India: Prentice Hall of India Pvt. Ltd.
24. Edgar, T.F., Himmelblau, D.M., and Lasdon, L.S. (2001), Optimization of chemical processes, New York: McGraw-Hill.
25. Eshelman, L.J. (1991), The CHC adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination, Foundations of Genetic Algorithms 1 (FOGA-1), 265-283.
26. Floudas, C.A. (1995), Nonlinear and mixed-integer optimization, New York: Oxford University.
27. Garrard, A., and Fraga, E.S. (1998), Mass exchange network synthesis using genetic algorithms, Computers and Chemical Engineering, 22(12), 1837-1850.
28. Glover, F. (1986), Future paths for integer programming and links to artificial intelligence, Comput. Oper. Res., 13, 533-549.
29. Goldberg, D.E. (2001), Genetic algorithms in search, optimization, and machine learning, Delhi, India: Pearson Education Pte. Ltd.
30. Goldberg, D.E., and Deb, K. (1991), A Comparison of selection schemes used in genetic algorithms, In Foundations of Genetic Algorithms 1 (FOGA-1), 69-93.
31. Grossmann, I.E., and Sargent, Roger W.H. (1979), Optimum Design of Multipurpose Chemical Plants, Ind. Eng. Chem. Process Des. Dev., 18(2), 343-348.
32. Hansen, P. (1986), The steepest ascent mildest heuristic for combinatorial programming, Congress on Numerical Methods in Combinatorial Optimization, Capri, Italy.
33. Hubert, R., Janiga, G., Baron, R., and Thévenin, D. (2006), Multi-objective shape optimization of heat exchanger using parallel genetic algorithms, International Journal of Heat and Mass Transfer, 49, 2567-2577.
34. Holland, J.H. (1975), Adaptation in natural and artificial systems, Ann Arbour: University of Michigan Press.
35. Kasat, Rahul B., Kunzru, D., Saraf, D. N. and Gupta, Santosh K. (2002), Multiobjective optimization of industrial FCC units using elitist nondominated sorting genetic algorithm, Ind. Eng. Chem. Res., 41, 4765-4776.
36. Kim, M., Jung, J.H., and Lee, In-Beum. (1996), Intelligent scheduling and monitoring for multi-product networked batch processes, Computers and Chemical Engineering, 20 Suppl., S1149-S1154.
37. Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P. (1983), Optimization by simulated annealing, Science, 220, 671-680.
38. Ku, H.M., and Karimi, I. (1991), An evaluation of simulated annealing for batch scheduling, Ind. Eng. Chem. Res., 30(1), 163-169.
39. Löhl, T., Schulz, C., and Engell, S. (1998), Sequencing of batch operations for a highly coupled production process: Genetic algorithms versus mathematical programming, Computers and Chemical Engineering, 22 Suppl., S579-S585.
40. Low, K.H., and Sorensen, E. (2004), Simultaneous optimal design and operation of multipurpose batch distillation columns, Chemical Engineering and Processing, 43, 273-289.
41. Luus, R. (1993a), Application of dynamic programming to differential algebraic process systems, Computers and Chemical Engineering, 17, 373-377.
42. Luus, R. (1993b), Optimization of heat exchanger networks, Ind. Eng. Chem. Res., 32, 2633-2635.
43. Méndez, C.A., Cerda, J., Grossmann, I.E., Harjunkoski, I., and Fahl, M. (2006), State- of-the-art review of optimization methods for short-term scheduling of batch processes, Computers and Chemical Engineering, 30, 913-946.
44. nd ed.), Berlin, Germany: Springer.
45. Mitchell, M. (2005), An Introduction to Genetic Algorithms, New Delhi, India: Prentice Hall of India Pvt. Ltd.
46. Ozyurt, B., Mogili, P., Mierau, B., Sunol, S.G., and Sunol, A.K. (1996), A hierarchical approach to simultaneous design of products and processes, Computers and Chemical Engineering, 20 Suppl., S73-S78.
47. Rajesh, J. K., Gupta, Santosh K., Rangaiah, G. P. and Ray, Ajay K. (2000), Multiobjective optimization of steam reformer performance using genetic algorithm, Ind. Eng. Chem. Res., 39, 706-717.
48. Ravi,G., Gupta, Santosh K., and Ray, M. B. (2000), Multiobjective optimization of cyclone separators using genetic algorithm, Ind. Eng. Chem. Res., 39, 4272-4286.
49. Reklaitis, G.V., Ravindran, A., and Ragsdell, K.M. (1983), Engineering optimization methods and applications, New York: Wiley.
50. Salcedo, R.L. (1992), Solving nonconvex nonlinear programming and mixed integer nonlinear programming problems with adaptive random search, Ind. Eng. Chem. Res., 31(1), 262-273.
51. Samuel, D., Pibouleau, L., Azzaro-Pantel, C., and Domenech, S. (2003), Design and retrofit of multiobjective batch plants via a multicriteria genetic algorithm, Computers and Chemical Engineering, 27, 1723-1740.
52. Shopova, E.G., and Natasha G. Vaklieva-Bancheva (2006), BASIC-A genetic algorithm for engineering problems solution, Computers and Chemical Engineering, 30, 1293-1309.
53. Summanwar, V.S., Jayaram, V. K., Kulkarni, B. D., Kusumakar, H. S., Gupta, K., and Rajesh, J. (2002), Solution of constrained optimization problems by multi-objective genetic algorithm, Computers and Chemical Engineering, 26, 1481-1492.
54. Tarafder, A., Lee, Bennett C. S., Ray, Ajay K. and Rangaiah, G. P. (2005), Multiobjective optimization of an industrial ethylene reactor using a nondominated sorting genetic algorithm, Ind. Eng. Chem. Res., 44, 124-141.
55. Tayal, M.C., and Fu, Y. (1999), Optimal design of heat exchangers: a genetic algorithm framework, Ind. Eng. Chem. Res., 38, 456-467.
56. Upreti, S.R., and Deb, K. (1997), Optimal design of an ammonia synthesis reactor using genetic algorithms, Computers and Chemical Engineering, 21(1), 87-92.
57. Wang, C., Quan, H., and Xu, X. (1996), Optimal design of multiproduct batch chemical process using genetic algorithms, Ind. Eng. Chem. Res., 35, 3560-3566.
58. Wang, C., Quan, H., and Xu, X. (1999), Optimal design of multiproduct batch chemical processes using tabu search, Computers and Chemical Engineering, 23, 427-437.
59. Wang, K., Löhl, T., Stobbe, M., and Engell, S. (2000), A genetic algorithm for online-scheduling of a multiproduct polymer batch plant, Computers and Chemical Engineering, 24, 393-400.
60. Wodrich, M., and Bilchev, G., (1997), Cooperative distributed search: the ants way, Control and Cybernatics, 26(3), 413-445.