TY - GEN
T1 - Design of comminution circuits for improved productivity using a Multi-Objective Evolutionary Algorithm (MOEA)
AU - Mhlanga, Samson
AU - Ndlovu, Jabulani
AU - Mbohwa, Charles
AU - Mutingi, Michael
PY - 2011
Y1 - 2011
N2 - The performance of a processing plant has a large impact on the profitability of a mining operation, yet plant design optimisation decisions are based on past experience and intuition rather than on scientific analysis. Genetic algorithms as a tool for circuit analysis in plant design and optimisation was considered. The multi-objective evolutionary algorithm initialises the plant design and optimisation based on experimental results, which are used to formulate and determine the objective function values. A simulation was conducted to assess the performance of candidate solutions. The two optima are then traded-off using cost objective, which is sought to be minimized. Once an optimum was selected, the circuit mass balance and equipment design was performed, bringing the theory of network design and genetic algorithms into unison. Results of the study provide financial benefits, optimal parameter settings for the comminution equipment and ultimately better plant performance.
AB - The performance of a processing plant has a large impact on the profitability of a mining operation, yet plant design optimisation decisions are based on past experience and intuition rather than on scientific analysis. Genetic algorithms as a tool for circuit analysis in plant design and optimisation was considered. The multi-objective evolutionary algorithm initialises the plant design and optimisation based on experimental results, which are used to formulate and determine the objective function values. A simulation was conducted to assess the performance of candidate solutions. The two optima are then traded-off using cost objective, which is sought to be minimized. Once an optimum was selected, the circuit mass balance and equipment design was performed, bringing the theory of network design and genetic algorithms into unison. Results of the study provide financial benefits, optimal parameter settings for the comminution equipment and ultimately better plant performance.
KW - Comminution circuits
KW - evolutionary algorithms
KW - multi-objective optimisation
UR - http://www.scopus.com/inward/record.url?scp=84856513747&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2011.6118202
DO - 10.1109/IEEM.2011.6118202
M3 - Conference contribution
AN - SCOPUS:84856513747
SN - 9781457707391
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 1680
EP - 1684
BT - IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
T2 - IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
Y2 - 6 December 2011 through 9 December 2011
ER -