%0 Journal Article
%T A genetic algorithm approach for open-pit mine production scheduling
%J International Journal of Mining and Geo-Engineering
%I University of Tehran
%Z 2345-6930
%A Alipour, Aref
%A khodaiari, Ali Asghar
%A Jafari, Ahmad
%A Tavakkoli-Moghaddam, Reza
%D 2017
%\ 06/01/2017
%V 51
%N 1
%P 47-52
%! A genetic algorithm approach for open-pit mine production scheduling
%K Open-Pit Mine
%K Production Scheduling
%K metaheuristic and genetic algorithm
%R 10.22059/ijmge.2017.62152
%X In an Open-Pit Production Scheduling (OPPS) problem, the goal is to determine the mining sequence of an orebody as a block model. In this article, linear programing formulation is used to aim this goal. OPPS problem is known as an NP-hard problem, so an exact mathematical model cannot be applied to solve in the real state. Genetic Algorithm (GA) is a well-known member of evolutionary algorithms that widely are utilized to solve NP-hard problems. Herein, GA is implemented in a hypothetical Two-Dimensional (2D) copper orebody model. The orebody is featured as two-dimensional (2D) array of blocks. Likewise, counterpart 2D GA array was used to represent the OPPS problemâ€™s solution space. Thereupon, the fitness function is defined according to the OPPS problemâ€™s objective function to assess the solution domain. Also, new normalization method was used for the handling of block sequencing constraint. A numerical study is performed to compare the solutions of the exact and GA-based methods. It is shown that the gap between GA and the optimal solution by the exact method is less than % 5; hereupon GA is found to be efficiently in solving OPPS problem.
%U https://ijmge.ut.ac.ir/article_62152_63f524d3a495f1be5547d320fdf13636.pdf