Calibration of Genetic Algorithm Parameters for Mining-Related Optimization Problems

Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on the selection of the GA parameter values (crossover and mutation rates and population size). We propose an approach based on full factorial and...

Full description

Saved in:

Bibliographic Details
Published in:	Natural resources research (New York, N.Y.) Vol. 28; no. 2; pp. 443 - 456
Main Authors:	Villalba Matamoros, Martha E., Kumral, Mustafa
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.04.2019 Springer Nature B.V
Subjects:	Algorithms Calibration Chemistry and Earth Sciences Computer Science Computing time Crossovers Earth and Environmental Science Earth Sciences Fossil Fuels (incl. Carbon Capture) Genetic algorithms Geography Heuristic methods Mathematical Modeling and Industrial Mathematics Mineral Resources Mutation Mutation rates Objective function Optimization Original Paper Parameters Physics Population number Response surface methodology Statistics for Engineering Sustainable Development Underground mines Underground mine planning Genetic algorithms (GA) Stope layout optimization Response surface methodology GA parameters
ISSN:	1520-7439, 1573-8981
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on the selection of the GA parameter values (crossover and mutation rates and population size). We propose an approach based on full factorial and response surface methodology experimental designs to calibrate GA parameters such that the objective function is maximized/minimized and the relative importance of the parameters is quantified. The approach was tested by applying it to stope optimization of underground mines, where profit can vary ± 7% based solely on GA parameters. Results showed that: (1) a larger population size did not always increase solution time; (2) solution time was positively related to crossover and mutation rates; and (3) simultaneous analysis of solution time and profit illustrated the trade-off between acceptable computing time and profit desirability through GA parameter selection. This approach can be used to calibrate parameters of other metaheuristics.
AbstractList	Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on the selection of the GA parameter values (crossover and mutation rates and population size). We propose an approach based on full factorial and response surface methodology experimental designs to calibrate GA parameters such that the objective function is maximized/minimized and the relative importance of the parameters is quantified. The approach was tested by applying it to stope optimization of underground mines, where profit can vary ± 7% based solely on GA parameters. Results showed that: (1) a larger population size did not always increase solution time; (2) solution time was positively related to crossover and mutation rates; and (3) simultaneous analysis of solution time and profit illustrated the trade-off between acceptable computing time and profit desirability through GA parameter selection. This approach can be used to calibrate parameters of other metaheuristics.
Author	Villalba Matamoros, Martha E. Kumral, Mustafa
Author_xml	– sequence: 1 givenname: Martha E. surname: Villalba Matamoros fullname: Villalba Matamoros, Martha E. organization: Department of Mining and Materials Engineering, McGill University – sequence: 2 givenname: Mustafa surname: Kumral fullname: Kumral, Mustafa email: mustafa.kumral@mcgill.ca organization: Department of Mining and Materials Engineering, McGill University
BookMark	eNp9kE9LAzEQxYNUsFU_gLcFz9H82XSzx1K0CpUWqeeQbGZryu6mJulBP71bVxAEPc0c5vfevDdBo853gNAVJTeUkOI2UkoEx4RKXPJSYHaCxlQUHMtS0tFxZwQXOS_P0CTGHekZLsUYbea6cSbo5HyX-TpbQAfJVdms2frg0mubrXXQLSQIMat9yJ5c57otfoZGJ7DZap9c6z4Gfh28aaCNF-i01k2Ey-95jl7u7zbzB7xcLR7nsyWuOJ0mLK0006KmwKFggtpc5BbElOTWMs1qzkxpjNC2YkTLWpuSWQ2sYtrktk_F-Dm6HnT3wb8dICa184fQ9ZaKlVRyRmVO-is6XFXBxxigVvvgWh3eFSXqWJ4aylN9eepYnjoqF7-YyqWvkClo1_xLsoGMvUu3hfDz09_QJywwhl8
CitedBy_id	crossref_primary_10_1007_s10479_023_05401_7 crossref_primary_10_1080_0305215X_2019_1624739 crossref_primary_10_3390_min12040437 crossref_primary_10_1007_s11053_021_09864_y crossref_primary_10_1007_s11771_019_4241_1 crossref_primary_10_1007_s11053_020_09628_0 crossref_primary_10_1108_DTA_10_2020_0256 crossref_primary_10_1080_17480930_2024_2325758
Cites_doi	10.1016/j.ejor.2012.05.029 10.1179/037178404225004940 10.1111/1467-9469.00174 10.1016/j.ejor.2014.07.040 10.1023/A:1010113930770 10.1016/j.asoc.2014.08.025 10.1179/174328607X228848 10.1057/palgrave.jors.2601902 10.1007/s11053-016-9296-1 10.1007/s11053-016-9301-8 10.1080/08982119608919043 10.1504/IJMME.2017.082680 10.1016/j.asoc.2015.11.038 10.1109/Tsmc.1986.289288 10.1007/0-306-48056-5_3 10.1016/j.talanta.2008.05.019 10.1016/j.aca.2007.07.011 10.1080/00224065.1980.11980968 10.1109/4235.771166 10.1111/j.2517-6161.1951.tb00067.x 10.1080/17480930.2018.1486692 10.1109/CEC.2007.4424460
ContentType	Journal Article
Copyright	International Association for Mathematical Geosciences 2018 International Association for Mathematical Geosciences 2018.
Copyright_xml	– notice: International Association for Mathematical Geosciences 2018 – notice: International Association for Mathematical Geosciences 2018.
DBID	AAYXX CITATION 8FE 8FG ABJCF AEUYN AFKRA ATCPS AZQEC BENPR BGLVJ BHPHI BKSAR CCPQU D1I DWQXO GNUQQ HCIFZ KB. PATMY PCBAR PDBOC PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PYCSY
DOI	10.1007/s11053-018-9395-2
DatabaseName	CrossRef ProQuest SciTech Collection ProQuest Technology Collection ProQuest Materials Science & Engineering ProQuest One Sustainability (subscription) ProQuest Central UK/Ireland Agricultural & Environmental Science Database ProQuest Central Essentials ProQuest Central Technology collection Natural Science Collection ProQuest SciTech Premium Collection‎ Natural Science Collection Earth, Atmospheric & Aquatic Science Collection ProQuest One Community College ProQuest Materials Science Collection ProQuest Central ProQuest Central Student SciTech Premium Collection Materials Science Database Environmental Science Database Earth, Atmospheric & Aquatic Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Environmental Science Collection
DatabaseTitle	CrossRef ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Central Essentials Materials Science Collection SciTech Premium Collection ProQuest One Community College ProQuest Central China Earth, Atmospheric & Aquatic Science Collection ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability Natural Science Collection ProQuest Central Korea Agricultural & Environmental Science Collection Materials Science Database ProQuest Central (New) ProQuest Materials Science Collection ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database ProQuest Technology Collection ProQuest SciTech Collection Environmental Science Collection ProQuest One Academic UKI Edition Materials Science & Engineering Collection Environmental Science Database ProQuest One Academic ProQuest One Academic (New)
DatabaseTitleList	ProQuest Central Student
Database_xml	– sequence: 1 dbid: KB. name: Materials Science Database url: http://search.proquest.com/materialsscijournals sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Geography Engineering Geology Physics Computer Science
EISSN	1573-8981
EndPage	456
ExternalDocumentID	10_1007_s11053_018_9395_2
GrantInformation_xml	– fundername: Natural Sciences and Engineering Research Council of Canada grantid: 242984 funderid: http://dx.doi.org/10.13039/501100000038
GroupedDBID	-5A -5G -BR -EM -~C .86 .VR 06D 0R~ 0VY 123 1N0 203 29M 2J2 2JN 2JY 2KG 2LR 2~H 30V 4.4 406 408 409 40D 40E 5VS 67M 67Z 6NX 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTV ABHLI ABHQN ABJCF ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABWNU ABXPI ACAOD ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACSNA ACZOJ ADHIR ADIMF ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEFQL AEGAL AEGNC AEJHL AEJRE AEMSY AEOHA AEPYU AESKC AETLH AEUYN AEVLU AEXYK AFBBN AFEXP AFKRA AFLOW AFQWF AFRAH AFWTZ AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AOCGG ARMRJ ASPBG ATCPS AVWKF AXYYD AYJHY AZFZN B-. BA0 BDATZ BENPR BGLVJ BGNMA BHPHI BKSAR BSONS CAG CCPQU CS3 CSCUP DDRTE DL5 DNIVK DPUIP EBLON EBS EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF I09 IJ- IKXTQ ITM IWAJR IXC IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KB. KDC KOV LAK LLZTM M4Y MA- N9A NPVJJ NQJWS NU0 O93 O9G O9I O9J OAM P19 PATMY PCBAR PDBOC PF0 PT4 PT5 PYCSY QOK QOS R89 R9I RNS ROL RPX RSV S16 S27 S3B SAP SDH SEV SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z5O Z7Y Z7Z Z81 Z85 Z86 Z8S Z8T Z8U Z8Z ZMTXR ~02 ~A9 ~KM -Y2 2.D 2P1 2VQ 5QI AAPKM AARHV AAYTO AAYXX ABBRH ABDBE ABFSG ABQSL ABRTQ ABULA ACBXY ACSTC ADHKG ADPHR AEBTG AEFIE AEKMD AEZWR AFDZB AFFHD AFGCZ AFHIU AFOHR AGGDS AGQPQ AHPBZ AHWEU AIXLP AJBLW ATHPR AYFIA CITATION COF H13 HZ~ IHE NDZJH O9- OVD PHGZM PHGZT PQGLB RNI RZC RZE RZK S1Z S26 S28 SCLPG T16 TEORI 8FE 8FG AZQEC D1I DWQXO GNUQQ PKEHL PQEST PQQKQ PQUKI PRINS
ID	FETCH-LOGICAL-c316t-8d8b67f1e3e7251d454de5604dd2a2f32b9bb5adc20a8fab92dae2c2ab4d98123
IEDL.DBID	RSV
ISICitedReferencesCount	12
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000460665100009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1520-7439
IngestDate	Wed Nov 05 08:39:04 EST 2025 Sat Nov 29 05:56:45 EST 2025 Tue Nov 18 21:50:02 EST 2025 Fri Feb 21 02:32:34 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	2
Keywords	Underground mine planning Genetic algorithms (GA) Stope layout optimization Response surface methodology GA parameters
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c316t-8d8b67f1e3e7251d454de5604dd2a2f32b9bb5adc20a8fab92dae2c2ab4d98123
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
PQID	2918321840
PQPubID	2043663
PageCount	14
ParticipantIDs	proquest_journals_2918321840 crossref_primary_10_1007_s11053_018_9395_2 crossref_citationtrail_10_1007_s11053_018_9395_2 springer_journals_10_1007_s11053_018_9395_2
PublicationCentury	2000
PublicationDate	20190401 2019-4-00
PublicationDateYYYYMMDD	2019-04-01
PublicationDate_xml	– month: 4 year: 2019 text: 20190401 day: 1
PublicationDecade	2010
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	Natural resources research (New York, N.Y.)
PublicationTitleAbbrev	Nat Resour Res
PublicationYear	2019
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	Snyman (CR30) 2005 Telford (CR31) 2007; 27 Ruiseco, Williams, Kumral (CR26) 2016; 25 Mitchell (CR18) 1999 Villalba, Kumral (CR33) 2017; 8 Eiben, Hinterding, Michalewicz (CR6) 1999; 3 Montgomery (CR19) 1997 Leite, Dimitrakopoulos (CR15) 2007; 116 CR35 CR34 Deutsch, Journel (CR5) 1998 Lamghari, Dimitrakopoulos (CR14) 2012; 222 CR32 Kumral (CR12) 2004; 113 Pandey, Chaudhary, Mehrotra (CR22) 2014; 24 Melvin (CR17) 2000 Goodfellow, Dimitrakopoulos (CR8) 2016; 40 Shi, Bloom, Mueller (CR28) 2000; 9 Ruiseco, Kumral (CR25) 2017; 26 Osman, Laporte (CR21) 1996 Derringer, Suich (CR4) 1980; 12 Kumral, Dowd (CR13) 2005; 56 Bezerra, Santelli, Oliveira, Villar, Escaleira (CR1) 2008; 76 Helland (CR10) 2000; 27 Sauvageau, Kumral (CR27) 2016; 32 Box, Wilson (CR2) 1951; 13 Reeves (CR24) 2003 Grefenstette (CR9) 1986; 16 Johnson, Wichern (CR11) 2007 Manchuk, Deutsch (CR16) 2008; 324 CR20 Shishvan, Sattarvand (CR29) 2015; 240 Clifton Young (CR3) 1996; 9 Ferreira, Bruns, Ferreira, Matos, David, Brandao (CR7) 2007; 597 Rayward-Smith, Rayward-Smith, Osman, Reeves, Smith (CR23) 1996 RA Johnson (9395_CR11) 2007 J Manchuk (9395_CR16) 2008; 324 M Kumral (9395_CR13) 2005; 56 M Mitchell (9395_CR18) 1999 ME Villalba (9395_CR33) 2017; 8 MA Bezerra (9395_CR1) 2008; 76 HM Pandey (9395_CR22) 2014; 24 RC Goodfellow (9395_CR8) 2016; 40 M Kumral (9395_CR12) 2004; 113 M Sauvageau (9395_CR27) 2016; 32 9395_CR32 MS Shishvan (9395_CR29) 2015; 240 JR Ruiseco (9395_CR25) 2017; 26 A Leite (9395_CR15) 2007; 116 A Lamghari (9395_CR14) 2012; 222 IS Helland (9395_CR10) 2000; 27 IH Osman (9395_CR21) 1996 9395_CR35 9395_CR34 C Reeves (9395_CR24) 2003 ÁE Eiben (9395_CR6) 1999; 3 JR Ruiseco (9395_CR26) 2016; 25 SL Ferreira (9395_CR7) 2007; 597 DC Montgomery (9395_CR19) 1997 T Melvin (9395_CR17) 2000 GE Box (9395_CR2) 1951; 13 B Shi (9395_CR28) 2000; 9 JJ Grefenstette (9395_CR9) 1986; 16 9395_CR20 J Snyman (9395_CR30) 2005 CV Deutsch (9395_CR5) 1998 VJ Rayward-Smith (9395_CR23) 1996 JK Telford (9395_CR31) 2007; 27 G Derringer (9395_CR4) 1980; 12 J Clifton Young (9395_CR3) 1996; 9
References_xml	– volume: 222 start-page: 642 issue: 3 year: 2012 end-page: 652 ident: CR14 article-title: A diversified Tabu search approach for the open-pit mine production scheduling problem with metal uncertainty publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2012.05.029 – year: 2007 ident: CR11 publication-title: Applied multivariate statistical analysis – volume: 113 start-page: A83 issue: 2 year: 2004 end-page: A88 ident: CR12 article-title: Optimal location of a mine facility by genetic algorithms publication-title: IMM Transactions, Mining Technology doi: 10.1179/037178404225004940 – volume: 27 start-page: 1 issue: 1 year: 2000 end-page: 20 ident: CR10 article-title: Model reduction for prediction in regression models publication-title: Scandinavian Journal of Statistics doi: 10.1111/1467-9469.00174 – volume: 240 start-page: 825 issue: 3 year: 2015 end-page: 836 ident: CR29 article-title: Long term production planning of open pit mines by ant colony optimization publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2014.07.040 – volume: 9 start-page: 53 issue: 1 year: 2000 end-page: 64 ident: CR28 article-title: Applications of conditional simulation to a positively skewed platinum mineralization publication-title: Natural Resources Research doi: 10.1023/A:1010113930770 – year: 2005 ident: CR30 publication-title: Practical mathematical optimization: An introduction to basic optimization theory and classical and new gradient-based algorithms – year: 1997 ident: CR19 publication-title: Design and analysis of experiments – volume: 24 start-page: 1047 year: 2014 end-page: 1077 ident: CR22 article-title: A comparative review of approaches to prevent premature convergence in GA publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2014.08.025 – ident: CR35 – volume: 116 start-page: 109 issue: 3 year: 2007 end-page: 118 ident: CR15 article-title: Stochastic optimisation model for open pit mine planning: Application and risk analysis at copper deposit publication-title: Mining Technology doi: 10.1179/174328607X228848 – volume: 56 start-page: 922 issue: 8 year: 2005 end-page: 930 ident: CR13 article-title: A simulated annealing approach to mine production scheduling publication-title: Journal of the Operational Research Society doi: 10.1057/palgrave.jors.2601902 – year: 1998 ident: CR5 publication-title: Geostatistical software library and user’s guide – volume: 25 start-page: 473 issue: 4 year: 2016 end-page: 485 ident: CR26 article-title: Optimizing ore–waste dig-limits as part of operational mine planning through genetic algorithms publication-title: Natural Resources Research doi: 10.1007/s11053-016-9296-1 – volume: 26 start-page: 23 issue: 1 year: 2017 end-page: 35 ident: CR25 article-title: A practical approach to mine equipment sizing in relation to dig-limit optimization in complex orebodies: Multi-rock type, multi-process, and multi-metal case publication-title: Natural Resources Research doi: 10.1007/s11053-016-9301-8 – volume: 32 start-page: 1 year: 2016 end-page: 19 ident: CR27 article-title: Genetic algorithms for the optimisation of the Schwartz-Smith two-factor model: A case study on a copper deposit publication-title: International Journal of Mining, Reclamation and Environment – volume: 9 start-page: 269 issue: 2 year: 1996 end-page: 277 ident: CR3 article-title: Blocking, replication, and randomization—The key to effective experimentation: A case study publication-title: Quality Engineering doi: 10.1080/08982119608919043 – year: 1999 ident: CR18 publication-title: An introduction to genetic algorithms – year: 1996 ident: CR21 publication-title: Metaheuristics: A bibliography – volume: 8 start-page: 1 issue: 1 year: 2017 end-page: 18 ident: CR33 article-title: Heuristic stope layout optimization accounting for variable stope dimensions and dilution management publication-title: International Journal of Mining and Mineral Engineering doi: 10.1504/IJMME.2017.082680 – volume: 13 start-page: 1 year: 1951 end-page: 45 ident: CR2 article-title: On the experimental attainment of optimum conditions publication-title: Journal of the Royal Statistical Society (Series B) – volume: 40 start-page: 292 year: 2016 end-page: 304 ident: CR8 article-title: Global optimization of open pit mining complexes with uncertainty publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2015.11.038 – volume: 16 start-page: 122 issue: 1 year: 1986 end-page: 128 ident: CR9 article-title: Optimization of control parameters for genetic algorithms publication-title: IEEE Transactions on Systems Man and Cybernetics doi: 10.1109/Tsmc.1986.289288 – volume: 27 start-page: 224 issue: 3 year: 2007 end-page: 232 ident: CR31 article-title: A brief introduction to design of experiments publication-title: Johns Hopkins APL Technical Digest – start-page: 55 year: 2003 end-page: 82 ident: CR24 article-title: Genetic algorithms publication-title: Handbook of metaheuristics doi: 10.1007/0-306-48056-5_3 – ident: CR32 – year: 2000 ident: CR17 publication-title: Response surface optimization using JMP Software – ident: CR34 – volume: 76 start-page: 965 issue: 5 year: 2008 end-page: 977 ident: CR1 article-title: Response surface methodology (RSM) as a tool for optimization in analytical chemistry publication-title: Talanta doi: 10.1016/j.talanta.2008.05.019 – volume: 597 start-page: 179 issue: 2 year: 2007 end-page: 186 ident: CR7 article-title: Box–Behnken design: An alternative for the optimization of analytical methods publication-title: Analytica Chimica Acta doi: 10.1016/j.aca.2007.07.011 – volume: 12 start-page: 214 issue: 4 year: 1980 end-page: 219 ident: CR4 article-title: Simultaneous optimization of several response variables publication-title: Journal of Quality Technology doi: 10.1080/00224065.1980.11980968 – volume: 3 start-page: 124 issue: 2 year: 1999 end-page: 141 ident: CR6 article-title: Parameter control in evolutionary algorithms publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.771166 – volume: 324 start-page: 67 year: 2008 end-page: 75 ident: CR16 article-title: Optimizing stope designs and sequences in underground mines publication-title: SME Transactions – ident: CR20 – start-page: 1 year: 1996 end-page: 25 ident: CR23 article-title: Modern heuristic techniques publication-title: Modern heuristic search methods – volume: 113 start-page: A83 issue: 2 year: 2004 ident: 9395_CR12 publication-title: IMM Transactions, Mining Technology doi: 10.1179/037178404225004940 – volume-title: Metaheuristics: A bibliography year: 1996 ident: 9395_CR21 – volume: 13 start-page: 1 year: 1951 ident: 9395_CR2 publication-title: Journal of the Royal Statistical Society (Series B) doi: 10.1111/j.2517-6161.1951.tb00067.x – volume: 12 start-page: 214 issue: 4 year: 1980 ident: 9395_CR4 publication-title: Journal of Quality Technology doi: 10.1080/00224065.1980.11980968 – volume: 76 start-page: 965 issue: 5 year: 2008 ident: 9395_CR1 publication-title: Talanta doi: 10.1016/j.talanta.2008.05.019 – volume: 597 start-page: 179 issue: 2 year: 2007 ident: 9395_CR7 publication-title: Analytica Chimica Acta doi: 10.1016/j.aca.2007.07.011 – volume: 3 start-page: 124 issue: 2 year: 1999 ident: 9395_CR6 publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.771166 – volume: 240 start-page: 825 issue: 3 year: 2015 ident: 9395_CR29 publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2014.07.040 – volume-title: Response surface optimization using JMP Software year: 2000 ident: 9395_CR17 – volume-title: An introduction to genetic algorithms year: 1999 ident: 9395_CR18 – volume: 56 start-page: 922 issue: 8 year: 2005 ident: 9395_CR13 publication-title: Journal of the Operational Research Society doi: 10.1057/palgrave.jors.2601902 – ident: 9395_CR32 – volume: 25 start-page: 473 issue: 4 year: 2016 ident: 9395_CR26 publication-title: Natural Resources Research doi: 10.1007/s11053-016-9296-1 – volume: 32 start-page: 1 year: 2016 ident: 9395_CR27 publication-title: International Journal of Mining, Reclamation and Environment – volume: 24 start-page: 1047 year: 2014 ident: 9395_CR22 publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2014.08.025 – volume: 8 start-page: 1 issue: 1 year: 2017 ident: 9395_CR33 publication-title: International Journal of Mining and Mineral Engineering doi: 10.1504/IJMME.2017.082680 – volume: 324 start-page: 67 year: 2008 ident: 9395_CR16 publication-title: SME Transactions – volume: 26 start-page: 23 issue: 1 year: 2017 ident: 9395_CR25 publication-title: Natural Resources Research doi: 10.1007/s11053-016-9301-8 – volume: 9 start-page: 269 issue: 2 year: 1996 ident: 9395_CR3 publication-title: Quality Engineering doi: 10.1080/08982119608919043 – volume: 16 start-page: 122 issue: 1 year: 1986 ident: 9395_CR9 publication-title: IEEE Transactions on Systems Man and Cybernetics doi: 10.1109/Tsmc.1986.289288 – volume: 27 start-page: 1 issue: 1 year: 2000 ident: 9395_CR10 publication-title: Scandinavian Journal of Statistics doi: 10.1111/1467-9469.00174 – volume: 40 start-page: 292 year: 2016 ident: 9395_CR8 publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2015.11.038 – ident: 9395_CR34 doi: 10.1080/17480930.2018.1486692 – volume-title: Geostatistical software library and user’s guide year: 1998 ident: 9395_CR5 – volume: 116 start-page: 109 issue: 3 year: 2007 ident: 9395_CR15 publication-title: Mining Technology doi: 10.1179/174328607X228848 – volume: 9 start-page: 53 issue: 1 year: 2000 ident: 9395_CR28 publication-title: Natural Resources Research doi: 10.1023/A:1010113930770 – volume-title: Applied multivariate statistical analysis year: 2007 ident: 9395_CR11 – volume-title: Practical mathematical optimization: An introduction to basic optimization theory and classical and new gradient-based algorithms year: 2005 ident: 9395_CR30 – start-page: 1 volume-title: Modern heuristic search methods year: 1996 ident: 9395_CR23 – volume: 27 start-page: 224 issue: 3 year: 2007 ident: 9395_CR31 publication-title: Johns Hopkins APL Technical Digest – volume-title: Design and analysis of experiments year: 1997 ident: 9395_CR19 – ident: 9395_CR20 doi: 10.1109/CEC.2007.4424460 – ident: 9395_CR35 – volume: 222 start-page: 642 issue: 3 year: 2012 ident: 9395_CR14 publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2012.05.029 – start-page: 55 volume-title: Handbook of metaheuristics year: 2003 ident: 9395_CR24 doi: 10.1007/0-306-48056-5_3
SSID	ssj0007385
Score	2.2257411
Snippet	Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	443
SubjectTerms	Algorithms Calibration Chemistry and Earth Sciences Computer Science Computing time Crossovers Earth and Environmental Science Earth Sciences Fossil Fuels (incl. Carbon Capture) Genetic algorithms Geography Heuristic methods Mathematical Modeling and Industrial Mathematics Mineral Resources Mutation Mutation rates Objective function Optimization Original Paper Parameters Physics Population number Response surface methodology Statistics for Engineering Sustainable Development Underground mines
SummonAdditionalLinks	– databaseName: ProQuest Central dbid: BENPR link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LSwMxEB60KujBR1WsVsnBkxLcJtvt5iRVWj1oLVKhtyVPFfqyrYL_3mQ326pgL553E5adyeSbzOT7AE4Vr5ioGkosFathi28VFpxSHHMacGWoxagpZf5drdWKu13W9gduE99WmcfENFCroXRn5BeEOedz-cjl6A071ShXXfUSGsuw4pjKrJ-vXDVa7cdZLHZcLSljqk2SHPTO65rp5TkLLVwvkV3wlFUx-bkzzeHmrwppuvE0t_77yduw6SEnqmc-sgNLelCEjW9EhEVYu0kFfj93oeMua4nMLdDQIEdLbceheu_ZTj196aM2d_1cjpQTWcCL7lOFCZw21WmFHmwI6vu7naidqdVM9uCp2ehc32KvvIAlrURTHKtYRDVT0VTXLABSYTVU2mKjUCnCiaFEMCGqXEkS8NhwwYjimkjCRaiYhQx0HwqD4UAfAKrIKBBxFBliTMiDUMjYRDaHoSQwmsmgBEH-1xPpacmdOkYvmRMqO0Ml1lCJM1RCSnA2GzLKODkWvVzOjZP45TlJ5pYpwXlu3vnjPyc7XDzZEaxbPMWyxp4yFKbjd30Mq_Jj-joZn3jf_AJTrupg priority: 102 providerName: ProQuest
Title	Calibration of Genetic Algorithm Parameters for Mining-Related Optimization Problems
URI	https://link.springer.com/article/10.1007/s11053-018-9395-2 https://www.proquest.com/docview/2918321840
Volume	28
WOSCitedRecordID	wos000460665100009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVPQU databaseName: Earth, Atmospheric & Aquatic Science Database customDbUrl: eissn: 1573-8981 dateEnd: 20241213 omitProxy: false ssIdentifier: ssj0007385 issn: 1520-7439 databaseCode: PCBAR dateStart: 19970301 isFulltext: true titleUrlDefault: https://search.proquest.com/eaasdb providerName: ProQuest – providerCode: PRVPQU databaseName: Environmental Science Database customDbUrl: eissn: 1573-8981 dateEnd: 20241213 omitProxy: false ssIdentifier: ssj0007385 issn: 1520-7439 databaseCode: PATMY dateStart: 19970301 isFulltext: true titleUrlDefault: http://search.proquest.com/environmentalscience providerName: ProQuest – providerCode: PRVPQU databaseName: Materials Science Database customDbUrl: eissn: 1573-8981 dateEnd: 20241213 omitProxy: false ssIdentifier: ssj0007385 issn: 1520-7439 databaseCode: KB. dateStart: 19970301 isFulltext: true titleUrlDefault: http://search.proquest.com/materialsscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1573-8981 dateEnd: 20241213 omitProxy: false ssIdentifier: ssj0007385 issn: 1520-7439 databaseCode: BENPR dateStart: 19970301 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-8981 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007385 issn: 1520-7439 databaseCode: RSV dateStart: 19990301 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bS8MwFD54RX3wMhXnZeTBJyXSJW3XPG7iBdQ5vOFbydUJusk6Bf-9Sdo6FRX0rdAkLSfJyXfIOd8HsK143cRRKLFUrIEtvlVYcEpxwmnAlaEWo3rK_NNGu53c3rJOUcedldnu5ZWk99SjYjcLBVzuj92glEXY-t3JyJHNuBD98ubd_Tp6Fk-SauMih7bLq8zvhvh8GI0Q5pdLUX_WHC786y8XYb6AlqiZr4UlGNO9CiyUsg2o2MUVmPvAQViBmUIGvftagekjr_PrnnxmqMyW4cpVb4l8naC-QY6n2n4ANR_u-oP7YfcRdbhL8HIsncgiYHTmJSewz7LTCp1bn_RYFHuiTi5fk63A9eHB1f4xLqQYsKT1eIgTlYi4Yeqa6oZFRCqMQqUtWAqVIpwYSgQTIuJKkoAnhgtGFNdEEi5CxSyGoKsw0ev39BqguowDkcSxIcaEPAiFTExsgxpKAqOZDKoQlHOSyoKn3MllPKQjhmVn49TaOHU2TkkVdt67POUkHb813iwnOi32a5YS5lybi3arsFtO7Oj1j4Ot_6n1BsxavMXyxJ9NmBgOnvUWTMmX4X02qMFk66DduajB-Elrr-YX9Ru2je4R
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LTxsxEB7RUER7gJaHSHnUh_YCstjY3s36UCFoeYmQRlWQuC1-AhIkNElb5U_1N3a8D9IiwY1Dz7u25PXnmW_WM98AfLCq4ZNYGGqsbFLkt5ZqxTlNFY-U9Rw5ai6Z32q22-n5uexMwe-qFiakVVY2MTfUtm_CP_JtJgP4Qjyyc_edhq5R4Xa1aqFRwOLEjX9hyDb8dPwF9_cjYwf73c9HtOwqQA1vJCOa2lQnTd9w3DXRuVsRC-vQ7wtrmWKeMy21jpU1LFKpV1oyqxwzTGlhJbpDjvO-gGnBRRLXYHpvv935dm_7gzZMrtCKQVmg-tU9al6sh1Qm5C6hgeEypuxfTzihtw9uZHNHdzD_v32iNzBXUmqyW5yBtzDlegvw-i-hxQWYOcwbGI8XoRuK0XQBe9L3JMhu4ziye3OJSxld3ZKOCvlqQXSUIKEnp3kHDZonDTpLvqKJvS1rV0mn6MYzXIKzZ1ngMtR6_Z5bAdIwSaTTJPHMe6EioU3qE4zROIu8kyaqQ1TtcmZK2fXQ_eMmmwhGB2BkCIwsACNjddi8H3JXaI489fJaBYasND_DbIKEOmxVcJo8fnSyd09P9h5mj7qnrax13D5ZhVfIHWWRxLQGtdHgh1uHl-bn6Ho42CjPBYGL58bZH9cASZ8
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1JS8NAGP0Qdw8uVbGuc_CkDE1n0jRzLGpV1Frc8BZmtQVtSxMF_70zWayKCuItkGQSZvnmfcz73gPYVbxqgpovsVSsji2-VVhwSnHIqceVoRajppL55_VWK7y_Z-3c5zQu2O7FkWRW0-BUmnpJZaBMZVT4ZmGB4wHZxUpZDdsYPOHbRMZxuq6u795DsZNqSQVTbY7kkHdxrPldE583phHa_HJAmu47zYV___EizOeQEzWyObIEY7pXgoXCzgHlq7sEcx-0CUswk9ujd15LMHWc-v-6q5QxKuNluHFVXSKbP6hvkNOvth9AjceH_rCbdJ5Qmzvil1PvRBYZo4vUigKn7Dut0KWNVU95EShqZ7Y28QrcNo9uDk5wbtGAJa0GCQ5VKIK6qWqq6xYpKb_mK21BlK8U4cRQIpgQNa4k8XhouGBEcU0k4cJXzGILugrjvX5PrwGqysATYRAYYozPPV_I0AQ22aHEM5pJrwxeMT6RzPXLnY3GYzRSXnZ9HNk-jlwfR6QMe--vDDLxjt8e3iwGPcrXcRwR5kKey4LLsF8M8uj2j42t_-npHZhuHzaj89PW2QbMWkjGMm7QJownw2e9BZPyJenGw-10dr8ByLj3Yw
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Calibration+of+Genetic+Algorithm+Parameters+for+Mining-Related+Optimization+Problems&rft.jtitle=Natural+resources+research+%28New+York%2C+N.Y.%29&rft.au=Villalba+Matamoros%2C+Martha+E.&rft.au=Kumral%2C+Mustafa&rft.date=2019-04-01&rft.issn=1520-7439&rft.eissn=1573-8981&rft.volume=28&rft.issue=2&rft.spage=443&rft.epage=456&rft_id=info:doi/10.1007%2Fs11053-018-9395-2&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s11053_018_9395_2
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1520-7439&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1520-7439&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1520-7439&client=summon