Optimization of Oscillation Parameters in Continuous Casting Process of Steel Manufacturing: Genetic Algorithms Versus Differential Evolution
By:Arya K. Bhattacharya,Debjani Sambasivam
Published on 2009 by
The relationships between oscillation performance metrics like lubrication, oscillation mark depth and peak friction and the design parameter set consisting of stroke s, frequency f and deviation from sinusoidal waveform , are expressed in a mathematical framework. This enables the definition of explicit objective functions and constraints that are used to drive a Genetic Algorithm towards the best-performing parameter set across the entire range of casting speed. Comparison with parameter sets provided by OEM and implemented currently, shows that the synthesized set provides much better lubrication the prime objective of oscillating the mold while also reducing oscillation marks and peak friction. Furthermore, this is achieved with only minor variation of the parameters across the speed range. Substitution of a Genetic Algorithm by a Differential Evolution algorithm for the above synthesis generates exactly identical results from the engineering domain perspective, but with a convergence rate that is faster by at least one order of magnitude. The reasons for this are analyzed, leading to a conclusion that for small dimensioned problems DE is definitely a better approach, but for larger dimensioned ones it is advisable to use GA in the initial phases and switch to DE at a later stage as the approach to global optimum becomes asymptotic.
This Book was ranked at 26 by Google Books for keyword oscillating.
Book ID of Optimization of Oscillation Parameters in Continuous Casting Process of Steel Manufacturing: Genetic Algorithms Versus Differential Evolution's Books is QYeBoAEACAAJ, Book which was written byArya K. Bhattacharya,Debjani Sambasivamhave ETAG "7gm434uIi3Y"
Book which was published by since 2009 have ISBNs, ISBN 13 Code is 9789533070087 and ISBN 10 Code is 9533070080
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