Genetic Algorithms And Hydrometallurgical Equilibrium

The computation of hydrometallurgical equilibria is very difficult because of the many complex species in solution, the precipitates, condensed species, or solids, and the activity coefficient corrections necessary to non-ideal thermodynamics. Our objective was to tryout recently developed genetic algorithms to minimize free energy and solve the equilibrium computation. We selected test problems that were seemingly unsolvable with more traditional algorithms, and we applied genetic algorithms to them. We were pleased to find that genetic algorithms succeeded where other algorithms did not. We concluded that they are an effective tool for hydrometallurgical equilibria.