Approach to solving mining machine selection problem by using grey theory

Vladimir Milisavljevic; Alberto  Martinetti; Aleksander Cvjetic

doi:10.7494/miag.2018.3.535.59

Approach to solving mining machine selection problem by using grey theory

Vladimir Milisavljevic (Corresponding Author), Alberto Martinetti, Aleksander Cvjetic

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

The selection of a mining machine is a multiple-attribute problem that involves the consideration of numerous parameters of various origins. A common task in the mining industry is to select the best machine among several alternatives, which are frequently described both with numerical variables as well as linguistic variables.
Numerical variables are mostly related to the technical characteristics of the machines, which are available in detail in most cases. On the other hand, some equally important
parameters such as price, reliability, support for service and spare parts, operating cost, etc., are not available at the required level for various reasons; hence, these can be considered uncertain information. For this reason, such information is described with linguistic variables.
This paper presents research related to overcoming this problem by using grey theory for selecting a proper mining machine. Grey theory is a well-known method used for multiple-attribute selection problems that involves a system in which parts of the necessary information are known and parts are unknown.

Original language	English
Article number	5
Pages (from-to)	59-64
Number of pages	6
Journal	Mining - Informatics, Automation and Electrical Engineering
Volume	3
Issue number	535
DOIs	https://doi.org/10.7494/miag.2018.3.535.59
Publication status	Published - 2018

Keywords

machine selection
grey theory
multiple-attribute
uncertain information
mining industry
22/4 OA procedure

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10.7494/miag.2018.3.535.59

APPROACH TO SOLVING MINING MACHINES SELECTION PROBLEM BY USING GREY THEORY Final published version, 1.26 MBLicence: Taverne

Cite this

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title = "Approach to solving mining machine selection problem by using grey theory",

abstract = "The selection of a mining machine is a multiple-attribute problem that involves the consideration of numerous parameters of various origins. A common task in the mining industry is to select the best machine among several alternatives, which are frequently described both with numerical variables as well as linguistic variables.Numerical variables are mostly related to the technical characteristics of the machines, which are available in detail in most cases. On the other hand, some equally importantparameters such as price, reliability, support for service and spare parts, operating cost, etc., are not available at the required level for various reasons; hence, these can be considered uncertain information. For this reason, such information is described with linguistic variables.This paper presents research related to overcoming this problem by using grey theory for selecting a proper mining machine. Grey theory is a well-known method used for multiple-attribute selection problems that involves a system in which parts of the necessary information are known and parts are unknown.",

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T1 - Approach to solving mining machine selection problem by using grey theory

AU - Milisavljevic, Vladimir

AU - Martinetti, Alberto

AU - Cvjetic, Aleksander

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N2 - The selection of a mining machine is a multiple-attribute problem that involves the consideration of numerous parameters of various origins. A common task in the mining industry is to select the best machine among several alternatives, which are frequently described both with numerical variables as well as linguistic variables.Numerical variables are mostly related to the technical characteristics of the machines, which are available in detail in most cases. On the other hand, some equally importantparameters such as price, reliability, support for service and spare parts, operating cost, etc., are not available at the required level for various reasons; hence, these can be considered uncertain information. For this reason, such information is described with linguistic variables.This paper presents research related to overcoming this problem by using grey theory for selecting a proper mining machine. Grey theory is a well-known method used for multiple-attribute selection problems that involves a system in which parts of the necessary information are known and parts are unknown.

AB - The selection of a mining machine is a multiple-attribute problem that involves the consideration of numerous parameters of various origins. A common task in the mining industry is to select the best machine among several alternatives, which are frequently described both with numerical variables as well as linguistic variables.Numerical variables are mostly related to the technical characteristics of the machines, which are available in detail in most cases. On the other hand, some equally importantparameters such as price, reliability, support for service and spare parts, operating cost, etc., are not available at the required level for various reasons; hence, these can be considered uncertain information. For this reason, such information is described with linguistic variables.This paper presents research related to overcoming this problem by using grey theory for selecting a proper mining machine. Grey theory is a well-known method used for multiple-attribute selection problems that involves a system in which parts of the necessary information are known and parts are unknown.

KW - machine selection

KW - grey theory

KW - multiple-attribute

KW - uncertain information

KW - mining industry

KW - 22/4 OA procedure

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DO - 10.7494/miag.2018.3.535.59

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Approach to solving mining machine selection problem by using grey theory

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