Abstract
Bulk material blending systems still mostly implement static and non-reactive material blending methods like the well-known Chevron stacking. The optimization potential in the existing systems which can be made available using quality analyzing methods as online X-ray fluorescence measurement is inspected in detail in this paper using a multi-objective optimization approach based on steady state evolutionary algorithms. We propose various Baldwinian and Lamarckian repair algorithms, test them on real world problem data and deliver optimized solutions which outperform the standard techniques.
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Cipold, M.P., Shukla, P.K., Bachmann, C.C., Bao, K., Schmeck, H. (2012). An Evolutionary Optimization Approach for Bulk Material Blending Systems. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32937-1_48
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DOI: https://doi.org/10.1007/978-3-642-32937-1_48
Publisher Name: Springer, Berlin, Heidelberg
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