Multiobjective pareto optimization of an industrial straight grate iron ore induration process using an evolutionary algorithm

Materials and Manufacturing Processes

Volumn 24, Issue 3, 2009, Pages 331-342

  Mitra, Kishalay ^a   Majumder, Sushanta ^a   Runkana, Venkataramana ^b  

^a TATA CONSULTANCY SERVICES   (India)

^b TATA RESEARCH DEVELOPMENT AND DESIGN CENTRE   (India)

Author keywords

Induration process; Iron ore; Multiobjective optimization; Optimal control; Pareto

Indexed keywords

EVOLUTIONARY ALGORITHMS; HIGHWAY BRIDGES; IRON ORES; MODEL PREDICTIVE CONTROL; PARETO PRINCIPLE; PELLETIZING;

ABRASION INDICES; BED HEIGHTS; BURN-THROUGH; COLD COMPRESSIONS; DECISION VARIABLES; EMBEDDED RELATIONSHIPS; INDURATION PROCESS; IRON ORE; MODEL BASED PREDICTIVE CONTROLS; MULTI OBJECTIVES; OPERATING PRINCIPLES; OPERATIONAL CONSTRAINTS; OPTIMAL CONTROL; PARETO; PARETO OPTIMIZATIONS; PARETO-OPTIMAL; PELLET QUALITIES; PRESSURE AND TEMPERATURE PROFILES; STRAIGHT GRATES; TARGET POINTS; TUMBLER INDEXES;

MULTIOBJECTIVE OPTIMIZATION;

EID: 61449112056     PISSN: 10426914     EISSN: 15322475     Source Type: Journal    
DOI: 10.1080/10426910802679428     Document Type: Article

References (43)

1. Thurlby, J.A.; Batterham, R.J.; Turner, R.E. Development and validation of a mathematical model for the moving grate induration of iron pellets. International Journal of Mineral Processing 1979, 6, 43-64.
2. Kurtul, K.; Jules, T.; Daniel, H.; Guy, P.; Sylvain, C. Modelling of a pilot scale iron ore pellet induration furnace. Canadian Metallurgical Quarterly 1994, 33, 1-12.
3. Young, R.W.; Cross, M.; Gibson, R.D. Mathematical model of grate-kiln-cooler process used for induration of iron ore pellets. Ironmaking and Steelmaking 1979, 1, 1-13.
4. Davis, R.A.; Englund, D.J. Model and simulation of a ported kiln for iron oxide pellet induration. The Canadian Journal of Chemical Engineering 2003, 81, 86-93.
5. Cross, M.; Patel, M.K.; Wade, K.C.; Analysis of the gas flow and heat distribution in iron ore pellet induration systems. In R.K. Rajamani, J.A. Herbst (Eds.), Control 90. Mineral and Metallurgical Processing 1990, 99-107.
6. Dwarapudi, S.; Gupta, P.K.; Mohan Rao, S. Prediction of iron ore pellet strength using artificial neural network model. ISIJ International 2007, 47, 67-72.
7. Pomerleau, D.; Pomerleau, A.; Hodouin, D.; Poulin, E. A procedure for the design and evaluation of decentralized and model-based predictive multivariable controllers for a pellet cooling process. Computers and Chemical Engineering 2003, 27, 217-233.
8. Chakraborti, N.; Deb, K.; Jha, A. A genetic algorithm based heat transfer analysis of a bloom re-heating furnace. Steel Research 2000, 71 (10), 396-402.
9. Broughton, J.S.; Mahfouf, M.; Linkens, D.A. A paradigm for the scheduling of a continuous walking beam reheat furnace using a modified genetic algorithm. Mater. Manuf. Process. 2007, 22 (5), 607-614.
10. Coello, C.A.; Veldhuizen, D.; Lamont, G. Evolutionary Algorithms for Solving Multi-Objective Problems; Kluwer Academic Publishers, 2002.
11. Deb, K. Multi-Objective Optimization Using Evolutionary Algorithms; Wiley: Chichester, UK, 2001.
12. Deb, K. Unveiling innovative design principles by means of multiple conflicting objectives. Engineering Optimization 2003, 35, 445-470.
13. Miettinen, K. Nonlinear Multi-Objective Optimization; Kluwer: Boston, 1999.
14. Chankong, V.; Haimes, Y.Y. Multi-Objective Decision Making: Theory and Methodology; Elsevier: New York, 1983.
15. Deb, K.; Pratap, A.; Agarwal, S.; Meyarivan, T. A fast and elitist multi-objective genetic algorithms. IEEE Transactions on Evolutionary Computation 2002, 6, 181-197.
16. Zitzler, E.; Thiele, L. Multi-objective evolutionary algorithms: A comparative case study and the Strength Pareto Approach. IEEE Transactions on Evolutionary Computation 1999, 3, 257-271.
17. Knowles, J.D.; Corne, D.W. Approximating the non-dominated front using the Pareto Archived Evolution Strategy. Evolutionary Computation Journal 2000, 8, 149-172.
18. Abbass, H.A.; Sarker, R.; Newton, C. PDE: A paretofrontier differential evolution approach for multi-objective optimization problems. In Proceedings of the Congress on Evolutionary Computation 2001 (CEC'2001). IEEE Sendce Center: Piscataway, New Jersey, 2001; Vol. 2, 971-978.
19. Abbass, H.A. The self-adaptive pareto differential evolution algorithm. In Congress on Evolutionary Computation (CEC'2002). IEEE Service Center: Piscataway, New Jersey, 2002; Vol. 1, 831-836.
20. Czyzak, P.; Jaszkiewicz, A. Pareto simulated annealing - A metaheuristic technique for multiple objective combinatorial optimization. J. Multi-Criteria Decision Anal. 1998, 7, 34-47.
21. Bandyopadhyay, S.; Saha, S.; Maulik, U.; Deb, K. A simulated annealing-based multiobjective optimization algorithm: AMOSA. IEEE Transactions on Evolutionary Computation 2008, 12 (3), 269-283.
22. Baran, B.; Schaerer, M. A multiobjective ant colony system for vehicle routing problem with time windows. Proc. Twenty first IASTED International Conference on Applied Informatics. Insbruck: Austria, 2003; 97-102.
23. Agarwal, A.; Gupta, S.K. Jumping gene adaptations of NSGA-II and their use in the multi-objective optimal design of shell and tube heat exchangers. Chemical Engineering Research & Design 2008, 86 (2), 123-139.
24. Chakraborti, N. Genetic algorithms in ferrous production metallurgy. Surveys on Mathematics for Industry 2002, 10, 269-291.
25. Chakraborti, N. Genetic algorithms in materials design and processing. Int. Mater. Rev. 2004, 49, 246-260.
26. Chakraborti, N. Genetic algorithms in these changing steel times. Ironmaking and Steelmaking 2005, 32, 401-404.
27. Mitra, K. Genetic algorithms in polymeric material production, design, processing and other applications. Accepted in International Materials Review 2008, 53, 275-297.
28. Kasat, R.B.; Ray, A.K.; Gupta, S.K. Applications of genetic algorithm in polymer science and engineering. Materials and Manufacturing Processes 2003, 18, 523-532.
29. Nandasana, A.D.; Ray, A.K.; Gupta, S.K. Applications of the Non-Dominated Sorting Genetic Algorithm (NSGA) in chemical reaction engineering. Intl. J. Chem. Rxn. Eng. 2003, 1 (R2), 1-16.
30. Majumder, S.; Natekar, P.V.; Runkana, V. Virtual indurator: A tool for simulation of induration of wet iron ore pellets on a moving grate. Accepted. Computers and Chemical Engineering 2008.
31. Ergun, S. Fluid flow through packed columns. Chemical Engineering Progress 1952, 48, 89-94.
32. Wynnyckyj, J.R.; Batterham, R.J. Iron ore sintering and pellet induration processes. In 4th International Symposium on Agglomeration; Toronto, Canada, Capes, C.E., Ed.; Iron and Steel Soc., Inc.: Warrendale, PA, USA, 1985; 957-994.
33. Young, R.W. Dynamic mathematical model of sintering process. Ironmaking and Steelmaking 1977, 1, 321-328.
34. Treybal, R.C. Mass Transfer Operations; McGraw-Hill Book Co. Ltd.: Singapore, 1981.
35. Perry, R.H.; Chilton, C.H. Chemical Engineers Handbook, 4th Ed.; McGraw-Hill Book Co. Ltd.: New York, 1968.
36. Deb, K.; Mitra, K.; Dewri, R.; Majumdar, S. Towards a better understanding of the epoxy polymerization process using multi-objective evolutionary computation. Chemical Engineering Science 2004, 59, 4261-4277.
37. Mitra, K.; Gopinath, R. Multi-objective optimization of an industrial grinding operation using elitist non-dominated sorting genetic algorithm. Chemical Engineering Science 2004, 59, 385-396.
38. Nath, N.K.; Mitra, K. Mathematical modeling and optimization of two-layer sintering process for sinter quality and fuel efficiency by genetic algorithms. Materials and Manufacturing Processes 2005, 20, 335-349.
39. Mitra, K.; Ghosh, S. Multi-objective optimization of spray cooling in an industrial thin slab casting machine using elitist genetic algorithm. Steel Grips 2005, 3, 111-119.
40. Majumdar, S.; Mitra, K.; Raha, S. Optimized species growth in epoxy polymerization using real coded NSGA II. Polymer 2005, 46, 11858-11869.
41. Majumdar, S.; Mitra, K.; Sardar, G. Kinetic analysis and optimization for the catalytic esterification step of PPT polymerization. Macromolecular Theory and Simulations 2005, 14, 49-59.
42. Mitra, K.; Majumdar, S. Selection of catalyst for the esterification step of the PPT polymerization process. Macromolecular Theory and Simulations 2006, 15, 497-506.
43. Deb, K.; Agrawal, R.B. Simulated binary crossover for continuous search space. Complex Systems 1995, 9, 115-148.