Long term production planning of open pit mines by ant colony optimization

The problem of long-term production planning of open pit mines is a large combinatorial problem. Application of mathematical programming approaches suffer from reduced computational efficiency due to the large amount of decision variables. This paper presents a new metaheuristic approximation approach based on the Ant Colony Optimization (ACO) for the solution of the problem of open-pit mine production planning. It is a three-dimensional optimization procedure which has the capability of considering any type of objective function, non-linear constraints and real technical restrictions. The proposed process is programmed and tested through its application on a real scale Copper-Gold deposit. The study revealed that the ACO approach is capable to improve the value of the initial mining schedule regarding the current commercial tools considering penalties and without, in a reasonable computational time. Several variants of ACO were examined to find the most compatible variants and the best parameter ranges. Results indicated that the Max-Min Ant System (MMAS) and the Ant Colony System (ACS) are the best possible variants based on the required less amount of memory. It is also proved that the MMAS is the most explorative variant, while the ACS is the fastest method.