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Alipour, Aref, khodaiari, Ali Asghar, Jafari, Ahmad, Tavakkoli-Moghaddam, Reza. (1396). A genetic algorithm approach for open-pit mine production scheduling. , 51(1), 47-52. doi: 10.22059/ijmge.2017.62152
Aref Alipour; Ali Asghar khodaiari; Ahmad Jafari; Reza Tavakkoli-Moghaddam. "A genetic algorithm approach for open-pit mine production scheduling". , 51, 1, 1396, 47-52. doi: 10.22059/ijmge.2017.62152
Alipour, Aref, khodaiari, Ali Asghar, Jafari, Ahmad, Tavakkoli-Moghaddam, Reza. (1396). 'A genetic algorithm approach for open-pit mine production scheduling', , 51(1), pp. 47-52. doi: 10.22059/ijmge.2017.62152
Alipour, Aref, khodaiari, Ali Asghar, Jafari, Ahmad, Tavakkoli-Moghaddam, Reza. A genetic algorithm approach for open-pit mine production scheduling. , 1396; 51(1): 47-52. doi: 10.22059/ijmge.2017.62152

A genetic algorithm approach for open-pit mine production scheduling

International Journal of Mining and Geo-Engineering
مقاله 6، دوره 51، شماره 1، شهریور 2017، صفحه 47-52    اصل مقاله (759.8 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/ijmge.2017.62152
نویسندگان
Aref Alipour* 1؛ Ali Asghar khodaiari2؛ Ahmad Jafari2؛ Reza Tavakkoli-Moghaddam3
1School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran
2School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.
3School of Industrial Engineering & Engineering Optimization Research Group, College of Engineering, University of Tehran, Tehran, Iran.
چکیده
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 problem’s solution space. Thereupon, the fitness function is defined according to the OPPS problem’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.
کلیدواژه‌ها
Open-Pit Mine؛ Production Scheduling؛ metaheuristic and genetic algorithm
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