Loading…
Mine fleet cost evaluation - Dijkstra's optimized path
Abstract The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consid...
Saved in:
Published in: | REM - International Engineering Journal 2019-06, Vol.72 (2), p.321-328 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333 |
---|---|
cites | cdi_FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333 |
container_end_page | 328 |
container_issue | 2 |
container_start_page | 321 |
container_title | REM - International Engineering Journal |
container_volume | 72 |
creator | Souza, Felipe Ribeiro Câmara, Taís Renata Torres, Vidal Félix Navarro Nader, Beck Galery, Roberto |
description | Abstract The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for calculating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Dijkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to increase for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning. |
doi_str_mv | 10.1590/0370-44672018720124 |
format | article |
fullrecord | <record><control><sourceid>scielo_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_1a2a0549e65246dcb088602a1cf64301</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><scielo_id>S2448_167X2019000300321</scielo_id><doaj_id>oai_doaj_org_article_1a2a0549e65246dcb088602a1cf64301</doaj_id><sourcerecordid>S2448_167X2019000300321</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333</originalsourceid><addsrcrecordid>eNpVkEtLA0EQhAdRMMT8Ai9787Sx57HzOEp8BSIeVPA2TGZ7deImE2Y2gv56d42IQtNdNFRRfIScUpjSysA5cAWlEFIxoHpYTByQERNCl1Sq58M_-phMcl4BADWcCS1HRN6FDRZNi9gVPuauwHfX7lwX4qYoi8uwestdcme5iNsurMMn1sXWda8n5KhxbcbJzx2Tp-urx9ltubi_mc8uFqXnVIiyYeDUUjVIUYuKUgVGMs05NFr5SiDXTCFqjnKpsFbMMO6MqWtdVbKmnPMxme9z6-hWdpvC2qUPG12w34-YXqxLXfAtWuqYg0oYlBUTsvZL0FoCc9Q3UnCgfdZ0n5V9wDbaVdylTV_ePgx87MCnh2d6OrwfNhj43uBTzDlh81uAgh3Q2wG9_Y-efwHVo3CA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Mine fleet cost evaluation - Dijkstra's optimized path</title><source>SciELO</source><creator>Souza, Felipe Ribeiro ; Câmara, Taís Renata ; Torres, Vidal Félix Navarro ; Nader, Beck ; Galery, Roberto</creator><creatorcontrib>Souza, Felipe Ribeiro ; Câmara, Taís Renata ; Torres, Vidal Félix Navarro ; Nader, Beck ; Galery, Roberto</creatorcontrib><description>Abstract The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for calculating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Dijkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to increase for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning.</description><identifier>ISSN: 2448-167X</identifier><identifier>EISSN: 2448-167X</identifier><identifier>DOI: 10.1590/0370-44672018720124</identifier><language>eng</language><publisher>Fundação Gorceix</publisher><subject>Dijkstra ; ENGINEERING, MECHANICAL ; fleet costs ; GEOLOGY ; MECHANICS ; METALLURGY & METALLURGICAL ENGINEERING ; optimized path ; transport distance ; transport time</subject><ispartof>REM - International Engineering Journal, 2019-06, Vol.72 (2), p.321-328</ispartof><rights>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333</citedby><cites>FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333</cites><orcidid>0000-0001-6804-9589 ; 0000-0002-7392-7291</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,24129,27901,27902</link.rule.ids></links><search><creatorcontrib>Souza, Felipe Ribeiro</creatorcontrib><creatorcontrib>Câmara, Taís Renata</creatorcontrib><creatorcontrib>Torres, Vidal Félix Navarro</creatorcontrib><creatorcontrib>Nader, Beck</creatorcontrib><creatorcontrib>Galery, Roberto</creatorcontrib><title>Mine fleet cost evaluation - Dijkstra's optimized path</title><title>REM - International Engineering Journal</title><addtitle>REM, Int. Eng. J</addtitle><description>Abstract The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for calculating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Dijkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to increase for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning.</description><subject>Dijkstra</subject><subject>ENGINEERING, MECHANICAL</subject><subject>fleet costs</subject><subject>GEOLOGY</subject><subject>MECHANICS</subject><subject>METALLURGY & METALLURGICAL ENGINEERING</subject><subject>optimized path</subject><subject>transport distance</subject><subject>transport time</subject><issn>2448-167X</issn><issn>2448-167X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkEtLA0EQhAdRMMT8Ai9787Sx57HzOEp8BSIeVPA2TGZ7deImE2Y2gv56d42IQtNdNFRRfIScUpjSysA5cAWlEFIxoHpYTByQERNCl1Sq58M_-phMcl4BADWcCS1HRN6FDRZNi9gVPuauwHfX7lwX4qYoi8uwestdcme5iNsurMMn1sXWda8n5KhxbcbJzx2Tp-urx9ltubi_mc8uFqXnVIiyYeDUUjVIUYuKUgVGMs05NFr5SiDXTCFqjnKpsFbMMO6MqWtdVbKmnPMxme9z6-hWdpvC2qUPG12w34-YXqxLXfAtWuqYg0oYlBUTsvZL0FoCc9Q3UnCgfdZ0n5V9wDbaVdylTV_ePgx87MCnh2d6OrwfNhj43uBTzDlh81uAgh3Q2wG9_Y-efwHVo3CA</recordid><startdate>20190601</startdate><enddate>20190601</enddate><creator>Souza, Felipe Ribeiro</creator><creator>Câmara, Taís Renata</creator><creator>Torres, Vidal Félix Navarro</creator><creator>Nader, Beck</creator><creator>Galery, Roberto</creator><general>Fundação Gorceix</general><scope>AAYXX</scope><scope>CITATION</scope><scope>GPN</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6804-9589</orcidid><orcidid>https://orcid.org/0000-0002-7392-7291</orcidid></search><sort><creationdate>20190601</creationdate><title>Mine fleet cost evaluation - Dijkstra's optimized path</title><author>Souza, Felipe Ribeiro ; Câmara, Taís Renata ; Torres, Vidal Félix Navarro ; Nader, Beck ; Galery, Roberto</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Dijkstra</topic><topic>ENGINEERING, MECHANICAL</topic><topic>fleet costs</topic><topic>GEOLOGY</topic><topic>MECHANICS</topic><topic>METALLURGY & METALLURGICAL ENGINEERING</topic><topic>optimized path</topic><topic>transport distance</topic><topic>transport time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Souza, Felipe Ribeiro</creatorcontrib><creatorcontrib>Câmara, Taís Renata</creatorcontrib><creatorcontrib>Torres, Vidal Félix Navarro</creatorcontrib><creatorcontrib>Nader, Beck</creatorcontrib><creatorcontrib>Galery, Roberto</creatorcontrib><collection>CrossRef</collection><collection>SciELO</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>REM - International Engineering Journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Souza, Felipe Ribeiro</au><au>Câmara, Taís Renata</au><au>Torres, Vidal Félix Navarro</au><au>Nader, Beck</au><au>Galery, Roberto</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mine fleet cost evaluation - Dijkstra's optimized path</atitle><jtitle>REM - International Engineering Journal</jtitle><addtitle>REM, Int. Eng. J</addtitle><date>2019-06-01</date><risdate>2019</risdate><volume>72</volume><issue>2</issue><spage>321</spage><epage>328</epage><pages>321-328</pages><issn>2448-167X</issn><eissn>2448-167X</eissn><abstract>Abstract The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for calculating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Dijkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to increase for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning.</abstract><pub>Fundação Gorceix</pub><doi>10.1590/0370-44672018720124</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-6804-9589</orcidid><orcidid>https://orcid.org/0000-0002-7392-7291</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2448-167X |
ispartof | REM - International Engineering Journal, 2019-06, Vol.72 (2), p.321-328 |
issn | 2448-167X 2448-167X |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_1a2a0549e65246dcb088602a1cf64301 |
source | SciELO |
subjects | Dijkstra ENGINEERING, MECHANICAL fleet costs GEOLOGY MECHANICS METALLURGY & METALLURGICAL ENGINEERING optimized path transport distance transport time |
title | Mine fleet cost evaluation - Dijkstra's optimized path |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T23%3A17%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-scielo_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mine%20fleet%20cost%20evaluation%20-%20Dijkstra's%20optimized%20path&rft.jtitle=REM%20-%20International%20Engineering%20Journal&rft.au=Souza,%20Felipe%20Ribeiro&rft.date=2019-06-01&rft.volume=72&rft.issue=2&rft.spage=321&rft.epage=328&rft.pages=321-328&rft.issn=2448-167X&rft.eissn=2448-167X&rft_id=info:doi/10.1590/0370-44672018720124&rft_dat=%3Cscielo_doaj_%3ES2448_167X2019000300321%3C/scielo_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3144-f20a7b7fe1e84511709628330f87c54e3827ee83e6b7ed72923a99dd8556d1333%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_scielo_id=S2448_167X2019000300321&rfr_iscdi=true |