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Production Scheduling of Open Pit Mines Using Particle Swarm Optimization Algorithm

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  • Asif Khan
  • Christian Niemann-Delius

Abstract

Determining an optimum long term production schedule is an important part of the planning process of any open pit mine; however, the associated optimization problem is demanding and hard to deal with, as it involves large datasets and multiple hard and soft constraints which makes it a large combinatorial optimization problem. In this paper a procedure has been proposed to apply a relatively new and computationally less expensive metaheuristic technique known as particle swarm optimization (PSO) algorithm to this computationally challenging problem of the open pit mines. The performance of different variants of the PSO algorithm has been studied and the results are presented.

Suggested Citation

  • Asif Khan & Christian Niemann-Delius, 2014. "Production Scheduling of Open Pit Mines Using Particle Swarm Optimization Algorithm," Advances in Operations Research, Hindawi, vol. 2014, pages 1-9, November.
  • Handle: RePEc:hin:jnlaor:208502
    DOI: 10.1155/2014/208502
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    Cited by:

    1. Zheng, Xiaolei & Nguyen, Hoang & Bui, Xuan-Nam, 2021. "Exploring the relation between production factors, ore grades, and life of mine for forecasting mining capital cost through a novel cascade forward neural network-based salp swarm optimization model," Resources Policy, Elsevier, vol. 74(C).
    2. Jiang Yao & Zhiqiang Wang & Hongbin Chen & Weigang Hou & Xiaomiao Zhang & Xu Li & Weixing Yuan, 2023. "Open-Pit Mine Truck Dispatching System Based on Dynamic Ore Blending Decisions," Sustainability, MDPI, vol. 15(4), pages 1-12, February.

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