An evolutionary optimization approach for bulk material blending systems

Michael P Cipold, Pradyumn Kumar Shukla, Claus C Bachmann, Kaibin Bao, Hartmut Schmeck

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.
Original languageUndefined
Title of host publicationInternational Conference on Parallel Problem Solving from Nature
PublisherSpringer Nature
Number of pages11
ISBN (Electronic)9783642329371
ISBN (Print)9783642329364
Publication statusPublished - 2012

Publication series

NameLecture Notes in Computer Science


  • Bulk material blending
  • Multi-objective evolutionary algorithms
  • Chevron stacking

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