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Optimization Strategies for Resource-Constrained Project Scheduling Problems in Underground Mining

Author

Listed:
  • Alessandro Hill

    (Department of Industrial and Manufacturing Engineering, California Polytechnic State University, San Luis Obispo, California 93407)

  • Andrea J. Brickey

    (Mining Engineering and Management, South Dakota School of Mines and Technology, Rapid City, South Dakota 57701)

  • Italo Cipriano

    (Alicanto Labs, Universidad Adolfo Ibáñez, Santiago 7941169, Chile)

  • Marcos Goycoolea

    (School of Business, Universidad Adolfo Ibáñez, Santiago 7941169, Chile)

  • Alexandra Newman

    (Department of Mechanical Engineering, Colorado School of Mines, Golden, Colorado 80401)

Abstract

Effective computational methods are important for practitioners and researchers working in strategic underground mine planning. We consider a class of problems that can be modeled as a resource-constrained project scheduling problem with optional activities; the objective maximizes net present value. We provide a computational review of math programming and constraint programming techniques for this problem, describe and implement novel problem-size reductions, and introduce an aggregated linear program that guides a list scheduling algorithm running over unaggregated instances. Practical, large-scale planning problems cannot be processed using standard optimization approaches. However, our strategies allow us to solve them to within about 5% of optimality in several hours, even for the most difficult instances.

Suggested Citation

  • Alessandro Hill & Andrea J. Brickey & Italo Cipriano & Marcos Goycoolea & Alexandra Newman, 2022. "Optimization Strategies for Resource-Constrained Project Scheduling Problems in Underground Mining," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3042-3058, November.
    • Handle: RePEc:inm:orijoc:v:34:y:2022:i:6:p:3042-3058
    DOI: 10.1287/ijoc.2022.1222
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    References listed on IDEAS

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