Optimising a production plan for underground coal mining: a genetic algorithm application
Supriyo Roy and
R.P. Mohanty
International Journal of Operational Research, 2021, vol. 41, issue 3, 423-445
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'.
Keywords: underground coal mining; production planning; optimisation; evolutionary search; genetic algorithm. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:41:y:2021:i:3:p:423-445
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