Genetic-Algorithm-Based Optimization of an Industrial Age-Hardening Operation for Packed Bundles of Aluminum Rods

REFERENCES

• Jaluria , Y. Thermal processing of materials: From basic research to engineering . J. Heat Transfer 2003 , 125 , 957 – 979 .
   Web of Science ®Google Scholar
• Sahay , S.S. Opportunities and challenges for process modeling in surface and heat treatment operations . Surface Engineering 2004 , 20 , 401 – 403 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Mitra , K. Cost model-based optimization of carburizing operation . Surface Eng. 2004 , 20 , 379 – 384 .
   Web of Science ®Google Scholar
• Malhotra , C.P. ; Pedanekar , N.R. ; Sahay , S.S. Cost model for the steel reheating operation . Industrial Heating March 2002 , 69 , 67 – 71 .
   Google Scholar
• Leden , B. A control system for fuel optimization of reheating furnaces. Scandinavian Journal of Metallurgy 1986, 15, 16–24.
   Google Scholar
• Sahay , S.S. ; Kumar , A.M. ; Chatterjee , A. Development of integrated model for batch annealing of cold rolled steels . Ironmaking Steelmaking 2004 , 31 , 144 – 152 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Krishnan , K. ; Kulthe , M. ; Chodha , A. ; Bhattacharya , A ; Das , A.K. Model-based optimization of a highly automated industrial batch annealing operation . Ironmaking Steelmaking 2006 , 33 , 306 – 314 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Krishnan , K. Model-based optimisation of a continuous annealing operation for a bundle of packed rods . Ironmaking Steelmaking 2007 , 34 , 89 – 94 .
   Web of Science ®Google Scholar
• Shercliff , H.R. ; Ashby , M.F. A process model for age-hardening of aluminum alloys-I . The Model. Acta Metall. Mater. 1990 , 38 , 1789 – 1802 .
   Web of Science ®Google Scholar
• Shercliff , H.R. ; Ashby , M.F. A process model for age-hardening of aluminum alloys-II. Applications of the model . Acta Metall. Mater. 1990 , 38 , 1803 – 1812 .
   Google Scholar
• Deschamps , A. ; Livet , F. ; Brechet , Y. Influence of prede-formation and ageing of an Al-Zn-Mg alloy-I. Microstruc-tural evolution and mechanical properties . Acta Materialia 1999 , 47 , 281 – 292 .
   Web of Science ®Google Scholar
• Deschamps , A. ; Brechet , Y. Influence of predeformation and ageing of an Al-Zn-Mg alloy-II. Modeling of precipitation kinetics and yield stress . Acta Materialia 1999 , 47 , 293 – 305 .
   Web of Science ®Google Scholar
• Krishnan , K. ; Sahay , S.S. Integrated model for industrial age-hardening operation for packed bundles of aluminium rods . To be submitted to Materials Manufacturing Processes .
   Google Scholar
• Davis , J.R. Aluminum and Aluminum Alloys, ASM Speciality Handbook ; ASM International , 1993 ; 311 pp .
   Google Scholar
• Holland , J.H. Adaptation in Natural and Artificial Systems ; University of Michigan Press : Ann Arbor , MI , 1975 .
   Google Scholar
• Goldberg , D.E. Genetic Algorithms in Search, Optimization and Machine Learning, , 6th Ed. ; Pearson Education : India , 2003 ; 10 pp .
   Google Scholar
• Deb , K. Multi-Objective Optimization Using Evolutionary Algorithms ; Wiley , Chichester : UK , 2001 ; 81 pp .
   Google Scholar
• Nath , N.K. ; Mitra , K. Mathematical modeling and optimization of two-layer sintering process for sinter quality and fuel efficiency by genetic algorithm . Materials and Manufacturing Processes 2005 , 20 , 335 – 349 .
   Web of Science ®Google Scholar
• Chakraborti , N. ; Gupta , R.S.P. ; Tiwari , T.K. Optimisation of continuous casting process using genetic algorithms: studies of spray and radiation cooling regions . Ironmaking Steelmaking 2003 , 30 , 273 – 278 .
   Web of Science ®Google Scholar
• Nandan , R. ; Rai , R. ; Jayakanth , R. ; Moitra , S. ; Chakraborti N. ; Mukhopadhyay , A. Regulating crown and flatness during hot rolling: A multiobjective optimization study using genetic algorithms . Mater. Manuf. Process. 2005 , 20 , 459 – 478 .
   Web of Science ®Google Scholar
• Chakraborti , N. Genetic algorithms in ferrous production metal-lurgy . Surveys on Mathematics for Industry 2002 , 10 , 269 – 291 .
   Google Scholar
• Chakraborti , N. New age process optimization: Genetic algorithms in these changing steel times . Ironmaking and Steelmaking 2005 , 32 , 401 – 404 .
   Web of Science ®Google Scholar
• Yagi , S. ; Kunii , D. Studies on effective thermal conductivities in packed beds . AIChE J. 1957 , 3 , 373 – 381 .
   Web of Science ®Google Scholar
• Kunii , D. ; Smith , J.M. Heat transfer characteristics of porous rocks . AIChE J. 1960 , 6 , 71 – 78 .
   Web of Science ®Google Scholar
• Patankar , S.V. Numerical Heat Transfer and Fluid Flow ; McGraw Hill , 1980 ; 71 pp .
   Google Scholar
• Jiao , S. ; Penning , J. ; Leysen , F. ; Houbaert , Y. ; Aernoudt , E. The modeling of the grain growth in a continuous reheating process of a low carbon Si-Mn bearing trip steel . ISIJ Int. 2000 , 40 , 1035 – 1040 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Malhotra , C.P. ; Kolkhede , A.M. Accelerated grain growth behavior during cyclic annealing . Acta Materialia 2003 , 51 , 339 – 346 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Krishnan , K. Analysis of the nonisothermal crystallization kinetics in three linear aromatic polyester systems . Thermochimica Acta 2005 , 430 , 23 – 29 .
   Web of Science ®Google Scholar
• Sahay , S.S. ; Joshi , K.M. Heating rate effects during nonisothermal annealing of AlK steel . Journal of Materials Engineering and Performance 2003 , 12 , 157 .
   Web of Science ®Google Scholar
• Deb , K. ; Agarwal , S. ; Pratap , A. ; Meyarivan , T. A fast and elitist multiobjective genetic algorithm: NSGA II , Technical Report 200001 ; Indian Institute of Technology, Kanpur Genetic Algorithms Laboratory (KanGAL) , 2000 ,
   Google Scholar
• Deb , K. ; Agarwal , S. ; Pratap , A. ; Meyarivan , T. A fast elitist nondominated sorting genetic algorithm for multiobjective optimization: NSGA II , In Proceedings of the Parallel Problem Solving form Nature VI (PPSN-VI) , Springer : NY , 2000 ; 849 – 858 .
   Google Scholar
• Deb , K. ; Pratap , A. ; Agarwal , S. ; Meyarivan , T. A fast and elitist multiobjective genetic algorithms . IEEE Transactions on Evolutionary Computation 2002 , 6 , 182 – 197 .
   Web of Science ®Google Scholar
• Deb , K. An efficient constraint handling method for genetic algorithms . Computer Methods in Applied Mechanics and Engineering 2000 , 186 , 311 – 338 .
   Web of Science ®Google Scholar
• Deb , K. ; Agarwal , R.B. Simulated binary crossover for continuous search space . Complex Systems 1995 , 9 , 115 – 148 .
   Google Scholar
• Deb , K. ; Kumar A. Real-coded genetic algorithms with simulated binary crossover: studies on multimodal and multiobjective problems . Complex Systems 1995 , 9 , 431 – 454 .
   Google Scholar