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Optimising a production plan for underground coal mining: a genetic algorithm application

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  • Supriyo Roy
  • R.P. Mohanty

Abstract

Developing an optimal production plan of an underground coal mine is complex due to several factors such as: economic, physical, environmental and social, etc. In this paper, an attempt has been made to apply genetic algorithm (GA) to maximise net present value (NPV) of a real life underground coal mine. It is first highlighted that the inefficacy of using direct optimisation methods and then a numerical illustration shows the efficacy of application of bio-inspired computation approach; because of its multiple advantages such as simplicity, user friendliness and parallel processing. This paper establishes the proposition that 'simulation-based stochastic optimisation for underground mine production plan would lead to better results than optimisation based on customary gradient optimisation approach'.

Suggested Citation

  • Supriyo Roy & R.P. Mohanty, 2021. "Optimising a production plan for underground coal mining: a genetic algorithm application," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 41(3), pages 423-445.
    • Handle: RePEc:ids:ijores:v:41:y:2021:i:3:p:423-445
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