A New Algorithm for the Open-Pit Mine Production Scheduling Problem

被引:106
|
作者
Chicoisne, Renaud [1 ]
Espinoza, Daniel [1 ]
Goycoolea, Marcos [2 ]
Moreno, Eduardo [3 ]
Rubio, Enrique [4 ,5 ]
机构
[1] Univ Chile, Dept Ind Engn, Santiago 8370439, Chile
[2] Univ Adolfo Ibanez, Sch Business, Santiago 7941169, Chile
[3] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago 7941169, Chile
[4] Univ Chile, Dept Min Engn, Santiago 8370439, Chile
[5] Univ Chile, Adv Min Technol Ctr, Santiago 8370439, Chile
关键词
MAXIMUM-FLOW PROBLEM; PSEUDOFLOW;
D O I
10.1287/opre.1120.1050
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
For the purpose of production scheduling, open-pit mines are discretized into three-dimensional arrays known as block models. Production scheduling consists of deciding which blocks should be extracted, when they should be extracted, and what to do with the blocks once they are extracted. Blocks that are close to the surface should be extracted first, and capacity constraints limit the production in each time period. Since the 1960s, it has been known that this problem can be cast as an integer programming model. However, the large size of some real instances (3-10 million blocks, 15-20 time periods) has made these models impractical for use in real planning applications, thus leading to the use of numerous heuristic methods. In this article we study a well-known integer programming formulation of the problem that we refer to as C-PIT. We propose a new decomposition method for solving the linear programming relaxation (LP) of C-PIT when there is a single capacity constraint per time period. This algorithm is based on exploiting the structure of the precedence-constrained knapsack problem and runs in O(mn log n) in which n is the number of blocks and m a function of the precedence relationships in the mine. Our computations show that we can solve, in minutes, the LP relaxation of real-sized mine-planning applications with up to five million blocks and 20 time periods. Combining this with a quick rounding algorithm based on topological sorting, we obtain integer feasible solutions to the more general problem where multiple capacity constraints per time period are considered. Our implementation obtains solutions within 6% of optimality in seconds. A second heuristic step, based on local search, allows us to find solutions within 3% in one hour on all instances considered. For most instances, we obtain solutions within 1-2% of optimality if we let this heuristic run longer. Previous methods have been able to tackle only instances with up to 150,000 blocks and 15 time periods.
引用
收藏
页码:517 / 528
页数:12
相关论文
共 50 条
  • [41] Dynamic optimization of open-pit coal mine production scheduling based on ARIMA and fuzzy structured element
    Liu, Guangwei
    Guo, Weiqiang
    Fu, Ensan
    Yang, Chuanda
    Li, Jiaming
    FRONTIERS IN EARTH SCIENCE, 2023, 10
  • [42] OPEN-PIT PLANNING AT ADAMS MINE
    WEST, FJ
    CANADIAN MINING AND METALLURGICAL BULLETIN, 1966, 59 (647): : 329 - &
  • [43] OPEN-PIT PRODUCTION SCHEDULER: ALGORITHM AND IMPLEMENTATION.
    Gershon, M.E.
    Mining Engineering, 1987, 39 (08) : 793 - 796
  • [44] Landslide mechanism and stability of an open-pit slope: The Manglai open-pit coal mine
    Chen, Tao
    Shu, Jisen
    Han, Liu
    Tovele, Gerson. S. V.
    Li, Baosheng
    FRONTIERS IN EARTH SCIENCE, 2023, 10
  • [45] Genetic Algorithm in Multimedia Dynamic Prediction of Groundwater in Open-Pit Mine
    Zhang, Runting
    Chen, Shuzhao
    Zhang, Zhouai
    Zhu, Wencheng
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [46] A NEW METAHEURISTIC ALGORITHM FOR LONG-TERM OPEN-PIT PRODUCTION PLANNING
    Sattarvand, Javad
    Niemann-Delius, Christian
    ARCHIVES OF MINING SCIENCES, 2013, 58 (01) : 107 - 118
  • [47] Blasting practices at the New Cornelia open-pit copper mine
    Angst, HH
    Cochrane, RA
    TRANSACTIONS OF THE AMERICAN INSTITUTE OF MINING AND METALLURGICAL ENGINEERS, 1943, 153 : 233 - 247
  • [48] Genetic Algorithm in Multimedia Dynamic Prediction of Groundwater in Open-Pit Mine
    Zhang, Runting
    Chen, Shuzhao
    Zhang, Zhouai
    Zhu, Wencheng
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [49] Genetic Algorithm in Multimedia Dynamic Prediction of Groundwater in Open-Pit Mine
    Zhang, Runting
    Chen, Shuzhao
    Zhang, Zhouai
    Zhu, Wencheng
    Computational Intelligence and Neuroscience, 2022, 2022
  • [50] GA-based Resource Transportation Scheduling Optimization of Open-pit Mine
    He Miao
    Zhou Jinsheng
    Nie Dexin
    2017 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA), 2017, : 247 - 250