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Comparative Study of Optimization Schemes in Mineral Processing Simulations
University of Borås, Faculty of Textiles, Engineering and Business.ORCID iD: 0000-0002-3283-067x
Chalmers tekniska högskola.
Chalmers tekniska högskola.
Chalmers tekniska högskola.
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2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
Sustainable development
According to the author(s), the content of this publication falls within the area of sustainable development.
Abstract [en]

Modelling and simulations for mineral processing plants have been successful in replicating and predicting predefined scenarios of an operating plant. However, there is a need to explore and increase the potential of such simulations to make them attractive for users. One of the tools to increase the attractiveness of the simulations is through applying optimization schemes. Optimization schemes, applied on mineral processing simulations, can identify non-intuitive solutions for a given problem. The problem definition itself is subjective in nature and is dependent on the purpose of the operating plant.The scope of this paper is to demonstrate two optimization schemes: Multi-Objective Optimization (MOO) using a Genetic Algorithm (GA) and Multi-Disciplinary Optimization (MDO) using an Individual Discipline Feasible (IDF) approach. A two stage coarse comminution plant is used as a case plant to demonstrate the applicability of the two optimization schemes. The two schemes are compared based on the problem formulations, types of result and computation time. Results show that the two optimization schemes are suitable in generating solutions to a defined problem and both schemes can be used together to produce complementary results.

Place, publisher, year, edition, pages
2018.
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:hb:diva-15654OAI: oai:DiVA.org:hb-15654DiVA, id: diva2:1278010
Conference
XXIX International Minerals Processing Congress Moscow, September 17-20, 2018
Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2019-01-14Bibliographically approved

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Bengtsson, Magnus

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