Particle swarm optimization approach for forecasting backbreak induced by bench blasting

Abstract

One of the most challenging safety problems in open pit mines is backbreak during blasting operation, and its prediction is very important for a technically and economically successful mining operation. This paper presents application of particle swarm optimization (PSO) technique to estimate the backbreak induced by bench blasting, based on major controllable blasting parameters. Two forms of PSO models, linear and quadratic, are developed based on blasting data from Sungun copper mine, Iran. According to obtained results, both models can be used to predict the backbreak, but the comparison of two models, in terms of statistical performance indices, shows that the quadratic form provides better results than the linear form.