Open Pit Production Scheduling applying Meta Heuristic approach

Abstract

Production scheduling of a mine is required for effective and economic operations of a mine. Here we are trying to perform production scheduling of mining of mineral blocks under some specific constraints to maximize the profit. The large number of variables and inequalities involved in the process makes it nearly impossible to solve using classical optimization techniques. The techniques and softwares available take a huge amount of time to produce optimized solutions. In this project Genetic Algorithm, a metaheuristic algorithm, has been considered to perform the optimization. The solution provided may not be optimized but will be very nearly optimized and will take significantly lesser time. It starts from a random solution performing several crossovers, mutations and eliminations to reach the optimized solution. A study was carried out in an open pit iron ore mine. The NPV of the mine was found to be a cumulative of over 551 million $. The average stripping ratio was calculated to be 1.72 over the period of 4 years. The computational time required to solve the problem was 31 mins. [math mode missing closing $]