Genetic Algorithm Rolling Mill Layout Optimization

REFERENCES

• Driraa , A. ; Pierrevala , H. ; Hajri-Gaboujb , S. Facility layout problems: A survey . Annual Reviews in Control 2007 , 31 ( 2 ), 255 – 267 .
   Web of Science ®Google Scholar
• Meller , D.R. ; Gau , K. The facility layout problem: Recent and emerging trends and perspectives . Journal of Manufacturing Systems 1996 , 15 ( 5 ), 351 – 366 .
   Web of Science ®Google Scholar
• McKendall , A.R. Jr. ; Hakobyan , A. Heuristics for the dynamic facility layout problem with unequal-area departments . European Journal of Operational Research 2010 , 201 ( 1 ), 171 – 182 .
   Web of Science ®Google Scholar
• Balakrishnan , J. ; Cheng , C.H. Dynamic layout algorithms: a state-of-the-art survey. Omega 1998, 26 (4), 507–521.
   Web of Science ®Google Scholar
• Chakraborti , N. ; Moitra , S. ; Mitra , A.; Mukhopadhyay, A. Evolutionary and genetic algorithms applied to hot rolling: A multi-objective rolling schedule studied using particle swarm algorithm . Transactions of the Indian Institute of Metals 2006 , 59 ( 5 ), 681 – 688 .
   Web of Science ®Google Scholar
• Önüta , S. ; Tuzkayaa , U.R. ; Doğaçb , B. A particle swarm optimization algorithm for the multiple-level warehouse layout design problem . Computers and Industrial Engineering 2008 , 54 ( 4 ), 783 – 799 .
   Web of Science ®Google Scholar
• Hani , Y. ; Amodeo , L. ; Yalaoui , F. ; Chen , H. Ant colony optimization for solving an industrial layout problem . European Journal of Operational Research 2007 , 183 ( 2 ), 633 – 642 .
   Web of Science ®Google Scholar
• Baykasoglu , A. ; Dereli , U. ; Sabuncu , I. An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems . Omega 2006 , 34 ( 4 ), 385 – 396 .
   Web of Science ®Google Scholar
• Mir , M. ; Imam , M.H. A hybrid optimization approach for layout design of unequal-area facilities . Computers and Industrial Engineering 2001 , 39 ( 1–2 ), 49 – 63 .
   Web of Science ®Google Scholar
• Braglia , M. Optimisation of a simulated-annealing-based heuristic for single row machine layout problem by genetic algorithm . International Transactions in Operational Research 1996 , 3 ( 1 ), 37 – 49 .
   Google Scholar
• Kouvelis , P. ; Chiang , W.C. ; Fitzsimmons , J. Simulated annealing for machine layout problems in the presence of zoning constraints . European Journal of Operational Research 1992 , 57 ( 2 ), 203 – 223 .
   Web of Science ®Google Scholar
• Azadeha , A. ; Moghaddama , M. ; Asadzadeha , S.M. ; Negahbanb , A. An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: The case of injection process with ambiguous data . European Journal of Operational Research 2011 , 214 ( 3 ), 768 – 779 .
   Web of Science ®Google Scholar
• Deb , S.K. ; Bhattacharyya , B. Fuzzy decision support system for manufacturing facilities layout planning . Decision Support Systems 2005 , 40 ( 2 ), 305 – 314 .
   Web of Science ®Google Scholar
• Liang , L.Y. ; Chao , W.C. The strategies of tabu search technique for facility layout optimization . Automation in Construction 2008 , 17 ( 6 ), 657 – 669 .
   Web of Science ®Google Scholar
• Shirazi , B. ; Fazlollahtabar , H. ; Sahebjamnia , N. Minimizing arbitrary earliness/tardiness penalties with common due date in single-machine scheduling problem using a tabu-geno-simulated annealing . Materials and Manufacturing Processes 2010 , 25 , 515 – 525 .
   Web of Science ®Google Scholar
• Gramegna , N. ; Della Corte , E. ; Poles , S. Manufacturing process simulation for product design chain optimization . Materials and Manufacturing Processes 2011 , 26 ( 3 ), 527 – 533 .
   Web of Science ®Google Scholar
• Nandan , R. ; Rai , R. ; Jayakanth , R. ; Moitra , S. ; Chakraborti , N. Regulating crown and flatness during hot rolling: A multiobjective optimization study using genetic algorithms . Materials and Manufacturing Processes 2005 , 20 ( 3 ), 459 – 478 .
   Web of Science ®Google Scholar
• Chakraborti , N. ; Kumar , B.S. ; Babu , V.S. ; Moitra , S. ; Mukhopadhyay , A. A new multi-objective genetic algorithm applied to hot-rolling process . Applied Mathematical Modelling 2005 , 32 ( 9 ), 1781 – 1789 .
   Web of Science ®Google Scholar
• Tam , K.Y. Genetic algorithms, function optimization, and facility layout design . European Journal of Operational Research 1992 , 63 ( 2 ), 322 – 346 .
   Web of Science ®Google Scholar
• Sadrzadeh , A. A genetic algorithm with the heuristic procedure to solve the multi-line layout problem . Computers and Industrial Engineering 2012 , 62 ( 4 ), 1055 – 1064 .
   Web of Science ®Google Scholar
• Kovačič , M. ; Uratnik , P. ; Brezočnik , M. ; Turk , R. Prediction of the bending capability of rolled metal sheet by genetic programming . Materials and Manufacturing Processes 2007 , 22 , 634 – 640 .
   Web of Science ®Google Scholar
• Kovačič , M. ; Šarler , B. Application of the genetic programming for increasing the soft annealing productivity in steel industry . Materials and Manufacturing Processes 2009 , 24 ( 3 ), 369 – 374 .
   Web of Science ®Google Scholar
• Kovačič , M. ; Šarler , B. Genetic algorithm-based batch filling scheduling in the steel industry . Materials and Manufacturing Processes 2011 , 26 ( 3 ), 464 – 474 .
   Web of Science ®Google Scholar
• Goldberg , D. Genetic Algorithms in Search, Optimisation and Machine Learning ; Addison-Wesley : Boston , MA , 1991 .
   Google Scholar
• Hachicha , W. A simulation metamodelling based neural networks for lot-sizing problem in MTO sector . International Journal of Simulation Modelling 2011 , 10 ( 4 ), 191 – 203 .
   Web of Science ®Google Scholar
• Xiao , J. ; Michalewicz , Z. ; Zhang , L. ; Trojanowski , K. Adaptive evolutionary planner/navigator for mobile robots . IEEE Transactions on Evolutionary Computation 1997 , 1 ( 1 ), 18 – 28 .
   Google Scholar