Multi‐Objective Genetic Algorithms and Genetic Programming Models for Minimizing Input Carbon Rates in a Blast Furnace Compared with a Conventional Analytic Approach

Data-driven models were constructed for the Productivity, CO2 emission, and Si content for an operational Blast furnace using evolutionary approaches that involved two recent strategies based upon bi-objective genetic Programming and neural nets evolving through Genetic Algorithms. The models were utilized to compute the optimum tradeoff between the level of CO2 emission and productivity at different Si levels, using a Predator–Prey Genetic Algorithm, well tested for computing the Pareto-optimality. The results were pitted against some similar calculations performed with commercial softwares and also compared with the results of thermodynamics-based analytical models.

[1]  Nirupam Chakraborti,et al.  Analyzing Leaching Data for Low-Grade Manganese Ore Using Neural Nets and Multiobjective Genetic Algorithms , 2009 .

[2]  Nirupam Chakraborti,et al.  Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives , 2013, Appl. Soft Comput..

[3]  Miran Brezocnik,et al.  Genetic Algorithm Rolling Mill Layout Optimization , 2013 .

[4]  David R. Anderson,et al.  Multimodel Inference , 2004 .

[5]  Nirupam Chakraborti,et al.  Data‐Driven Pareto Optimization for Microalloyed Steels Using Genetic Algorithms , 2012 .

[6]  Nirupam Chakraborti,et al.  Analysing blast furnace data using evolutionary neural network and multiobjective genetic algorithms , 2010 .

[7]  Nirupam Chakraborti,et al.  Modelling Noisy Blast Furnace Data using Genetic Algorithms and Neural Networks , 2006 .

[8]  H. K. D. H. Bhadeshia,et al.  Neural Networks in Materials Science , 1999 .

[9]  Ling Jian,et al.  A Sliding‐window Smooth Support Vector Regression Model for Nonlinear Blast Furnace System , 2011 .

[10]  Miran Brezocnik,et al.  Evolutionary Algorithm Approaches to Modeling of Flow Stress , 2011 .

[11]  Nirupam Chakraborti,et al.  Pareto-optimal analysis of Zn-coated Fe in the presence of dislocations using genetic algorithms , 2012 .

[12]  Mikko Helle,et al.  Multiobjective Optimization of Top Gas Recycling Conditions in the Blast Furnace by Genetic Algorithms , 2011 .

[13]  Carlo Poloni,et al.  Strength of Ferritic Steels: Neural Networks and Genetic Programming , 2008 .

[14]  Brahma Deo,et al.  Artificial neural nets for prediction of silicon content of blast furnace hot metal , 1996 .

[15]  Nirupam Chakraborti,et al.  Data-Driven Multiobjective Analysis of Manganese Leaching from Low Grade Sources Using Genetic Algorithms, Genetic Programming, and Other Allied Strategies , 2011 .

[16]  Nirupam Chakraborti,et al.  Analyzing Fe–Zn system using molecular dynamics, evolutionary neural nets and multi-objective genetic algorithms , 2009 .

[17]  Paul Zulli,et al.  CFD Modeling and Analysis of The Flow, Heat Transfer and Mass Transfer in a Blast Furnace Hearth , 2011 .

[18]  Henrik Saxén,et al.  Numerical Prediction of Iron Flow and Bottom Erosion in the Blast Furnace Hearth , 2012 .

[19]  Ujjwal Maulik,et al.  A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA , 2008, IEEE Transactions on Evolutionary Computation.

[20]  Nirupam Chakraborti,et al.  Phases in Zn-coated Fe analyzed through an evolutionary meta-model and multi-objective Genetic Algorithms , 2011 .

[21]  Dieter Janke,et al.  Thermodynamic modelling of the injection of waste products into a blast furnace , 2003 .

[22]  Frank Pettersson,et al.  Genetic Programming Evolved through Bi-Objective Genetic Algorithms Applied to a Blast Furnace , 2013 .

[23]  P. K. Sen,et al.  Approach for Minimizing Operating Blast Furnace Carbon Rate Using Carbon-Direct Reduction (C-DRR) Diagram , 2012, Metallurgical and Materials Transactions B.

[24]  Michitaka Sato,et al.  Optimization of Ironmaking Process for Reducing CO2 Emissions in the Integrated Steel Works , 2006 .

[25]  Frank Pettersson,et al.  A genetic algorithms based multi-objective neural net applied to noisy blast furnace data , 2007, Appl. Soft Comput..

[26]  Tatsuro Ariyama,et al.  Analysis on Non‐Uniform Gas Flow in Blast Furnace Based on DEM‐CFD Combined Model , 2011 .

[27]  Nirupam Chakraborti,et al.  Cu―Zn separation by supported liquid membrane analyzed through Multi-objective Genetic Algorithms , 2011 .