Multiple cut-off grade optimization by genetic algorithms and comparison with grid search method and dynamic programming

Abstract

Optimization of cut-off grades is a fundamental issue for mineral deposits. Determination of optimum cut-off grades, instead of application of a static cut-off grade for the life of a mine, maximizes the net present value. The authors describe the general problem of cut-off grade optimization for multi-mineral deposits and outline the use of genetic algorithms, the grid search method, and dynamic programming for optimal cut-off grade schedules for deposits with up to three constituent minerals. The methods are compared by assessing the results of the implications involved in using them.