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Multi-criteria decision making for the choice problem in mining and mineral processing: Applications and trends.

Authors :
Sitorus, Fernando
Cilliers, Jan J.
Brito-Parada, Pablo R.
Source :
Expert Systems with Applications. May2019, Vol. 121, p393-417. 25p.
Publication Year :
2019

Abstract

Highlights • MCDM has been useful to overcome the choice problem in mining and mineral processing. • AHP has been the most used MCDM technique in this area of research. • A large proportion of the published papers make use of hybrid methods. • This is the first review on the use of MCDM for the choice problem in this area. Abstract Despite the fact that the potential of multi-criteria decision making (MCDM) to overcome a variety of problems in mining and mineral processing has been widely recognised, no literature review in these fields has been conducted. This manuscript addresses this issue by providing a comprehensive overview of the applications and trends of MCDM methods for the choice problem (i.e., determining the best option from a set) in mining and mineral processing. 90 articles published between 1999 and 2017 were selected following a searching methodology and eligibility criteria detailed in this manuscript. In addition, for the purpose of the survey, different types of selection problems were identified. The results show that there are two phases of growth in the application of MCDM techniques to the choice problem in mining and mineral processing. The first phase, from 1999 to 2007, shows a very low number of publications with only a moderate increase by the end, whereas the second phase, from 2007 to 2017, shows a significant growth in the number of published articles. The review also shows that the most addressed problem has been the selection of mining methods, while the Analytical Hierarchy Process (AHP) has been the most used MCDM method. The rise in the application of hybrid MCDM methods is also discussed. This review paper provides insight into the current state of applications of MCDM in mining and mineral processing and discusses pathways for future research directions in the development of MCDM methods that would benefit these fields. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09574174
Volume :
121
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
134153166
Full Text :
https://doi.org/10.1016/j.eswa.2018.12.001