New cut optimization method at continuous casting
Applications of Large Scale Industrial Systems, Volume # 1 | Part# 1
J. Alatalo; E. Saarelainen; S. Sihvo
Digital Object Identifier (DOI)
steel industry,continuous casting,production systems,dynamic models,control algorithms,optimization problems,mathematical models
The paper covers main design principles and description of optimization algorithms for cutting steel at continuous casting plant. The aim is to produce maximum amount of customer bars from liquid steel. The static cutting plan from production planning is dynamically updated taking into account unexpected deviations in steel quality. The optimizing problem type is mixed integer non-linear programming (MINLP).
 Alatalo, J. (2006). Jatkuvavaletun teräksen leikkaussuunnitelman optimointi (Cutting plan optimization for continuous steel casting). Master's Thesis in Applied Mathematics, Department of Information Technology, Lappeenranta University of Technology. Will be published in autumn 2006.  Lampinen, J. and I. Zelinka (1999). Mixed integerdiscrete-continuous optimization by differential evolution, part 1: the optimization method. In: Ošmera, Pavel (ed.) (1999). Proceedings of MENDEL'99, 5th International Mendel Conference on Soft Computing pp. 71-76. Available via Internet: http://www.lut.fi/jlampine/MEND99p1.ps.  Pörn, R. (2000). Mixed Integer Non-Linear Programming: Convexification Techniques and Algorithm Development. PhD Thesis in Applied Mathematics, Department of Mathematics, bo Akademi University. Turku.  Price, K., R. Storn and J. Lampinen (2005). Differential evolution : a practical approach to global optimization. Berlin : Springer, cop.  Quesada, I. and I. Grossmann (1995). A global optimization algorithm for linear fractional and bilinear programs. Journal of Global Optimization 6, 39-76.  Ryoo, H. S. and N. V. Sahinidis (1995). Global optimization of non-convex nlps and minlps with application in process design. Computers & Chemical Engineering 19, 551-566.  Storn, R. and K. Price (1995). Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical report TR-95-012. Available via internet: ftp://ftp.icsi.berkeley.edu/ pub/techreports/1995/tr- 95-012.pdf.