Title: Mine-to-mill multi-objective optimal blending with technical and economic constraints using a modified genetic algorithm

Authors: Oscar Daniel Chuk; Carlos Gustavo Rodriguez Medina; Marina Romero; Luis Ventura Gutierrez; Juan Pedro Gil

Addresses: Facultad de Ingeniería, Instituto de Investigaciones Mineras, Universidad Nacional de San Juan, 5400, Argentina ' Facultad de Ingeniería, Instituto de Investigaciones Mineras, Universidad Nacional de San Juan, 5400, Argentina ' Facultad de Ingeniería, Instituto de Investigaciones Mineras, Universidad Nacional de San Juan, 5400, Argentina ' Facultad de Ingeniería, Instituto de Investigaciones Mineras, Universidad Nacional de San Juan, 5400, Argentina ' Facultad de Ingeniería, Instituto de Investigaciones Mineras, Universidad Nacional de San Juan, 5400, Argentina

Abstract: Optimisation techniques have been used effectively in the open pit mine planning. However, they are incorporated more slowly in the optimal solution of mine-to-mill blending. Specifically, no contributions are observed from the multi-objective approach. This work shows the application of a multi-objective genetic algorithm with additional non-natural genetic operations to the solution of this problem. The implementation of the algorithm in a particular case, but easily generalisable, is presented. The results show the efficiency of the procedure, with significant improvements in the Net Present Value.

Keywords: blending; mine-to-mill; optimisation; multi-objective; genetic algorithm; Net Present Value.

DOI: 10.1504/IJMME.2018.091968

International Journal of Mining and Mineral Engineering, 2018 Vol.9 No.2, pp.109 - 121

Received: 15 Sep 2017
Accepted: 10 Dec 2017
Published online: 23 May 2018 *

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