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

Authors: Supriyo Roy; R.P. Mohanty

Addresses: Birla Institute of Technology-Mesra, Ranchi, Jharkhand, India ' SOA University, Bhubaneswar, Odisha, India

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.

DOI: 10.1504/IJOR.2021.116264

International Journal of Operational Research, 2021 Vol.41 No.3, pp.423 - 445

Received: 19 Nov 2018
Accepted: 12 Jan 2019
Published online: 15 Jul 2021 *

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