Multiobjective Optimization of Manganese Recovery from Sea Nodules Using Genetic Algorithms

Abstract

Treatment of low grade manganese ores is receiving widespread attention due to major use of manganese (85–90%) as ferromanganese alloy in the rapidly growing iron and steel sector and also in other important industrial products like electrolytic manganese dioxide (EMD) used in the energy sector. Manganese bearing polymetallic sea nodules containing less than 40% Mn fall in the category of lean grade ores and besides manganese these nodules are the reserve for other metals like copper, nickel, and cobalt. In this present work, treatment of these polymetallic sea nodules in an acid-based hydrometallurgical route has been proposed using two different schemes, batch and parallel in nature. Both processes have been optimized using multiobjective genetic algorithms.