Application of genetic algorithms to the optimization of large mine ventilation networks

A computer program has been developed to determine the optimum combinations of main-fan pressure, booster-fan pressure and booster-fan position in a l arge mine ventilation network that will maintain specified fresh air flows and minimize total air-power consumption. The modular program, which combines application of a genetic-algorithm opti mization technique with a ventilation network simulator, has already been a pplied in a preliminary study of the optimization of a simple, representati ve mine ventilation network. That study is now extended by application of t he method to a large United Kingdom mine ventilation network. The results p roduced by the new study confirm that the selective rating of the main surf ace fan and rating and location of the booster fan can minimize the total p ower consumption and reduce the operating costs of the ventilation system.