Optimisation of opencast mining machinery noise using differential evolutionary algorithm Online publication date: Mon, 13-Nov-2017
by Debi Prasad Tripathy; D.S. Rao
International Journal of Mining and Mineral Engineering (IJMME), Vol. 8, No. 4, 2017
Abstract: Noise levels produced by various mining equipment's are high and exposure to such levels is considered as a severe problem. The aim of this paper is to develop and analyse the ability of a differential evolution (DE) algorithm to locate global optima of the far field noise levels produced by mining machineries in the mine. The objective function formulated is maximisation of sound pressure level (SPL) so as to determine optimal distance, optimal directivity index, optimal sound power level (SWL) and other optimal attenuation parameters. The most essential challenge in optimisation problems is CPU time. Comparison with the best known variants of DE over the objective function reflects the superiority of the parameter tuning scheme in terms of accuracy, convergence speed and robustness. Results show that DE/RAND/2 is able to converge, find optimum values faster compared to other mutation variants and seems to be a promising approach for machinery noise optimisation problems.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mining and Mineral Engineering (IJMME):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook