Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA)

A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the (1) remedial design co...

Full description

Saved in:

Bibliographic Details
Published in:	Advances in water resources Vol. 25; no. 1; pp. 51 - 65
Main Authors:	Erickson, Mark, Mayer, Alex, Horn, Jeffrey
Format:	Journal Article
Language:	English
Published:	Oxford Elsevier Ltd 2002 Elsevier Science
Subjects:	algorithms aquifers Computation Computational efficiency Contaminants Cost engineering Design engineering Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Exact sciences and technology Formulations Genetic algorithms groundwater contamination Groundwater remediation Hydrogeology Hydrology. Hydrogeology Mathematical models Pareto optimality pollution control Pollution, environment geology Pumping rates Remediation trichloroethylene water purification wells algorithms sensitivity analysis plumes ground water pollution contamination pumping remediation hydraulic conductivity aquifers water quality optimization design water resource management wells
ISSN:	0309-1708, 1872-9657
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the (1) remedial design cost and (2) contaminant mass remaining at the end of the remediation horizon. Three test scenarios consider pumping rates for two-, five-, and 15 fixed-location wells as the decision variables. A single objective genetic algorithm (SGA) formulation and a random search (RS) are also applied to the three scenarios to compare performances with NPGA. With 15 decision variables, the NPGA is demonstrated to outperform both the SGA algorithm and the RS by generating a better tradeoff curve. For example, for a given cost of $100,000, the NPGA solution found a design with 75% less mass remaining than the corresponding RS solution. In the 15-well scenario, the NPGA generated the full span of the Pareto optimal designs, but with 30% less computational effort than that required by the SGA. The RS failed to find any Pareto optimal solutions. The optimal population size for the NPGA was found by sensitivity analysis to be approximately 100, when the total computational cost was limited to 2000 function evaluations. The NPGA was found to be robust with respect to the other algorithm parameters (tournament size and niche radius) when using an optimal population size. The inclusion of niching produced better results in terms of covering the span of the tradeoff curve. As long as some niching was included, the results were insensitive to the value of the parameter that controls niching ( σ share>0).
AbstractList	A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the (1) remedial design cost and (2) contaminant mass remaining at the end of the remediation horizon. Three test scenarios consider pumping rates for two-, five-, and 15 fixed-location wells as the decision variables. A single objective genetic algorithm (SGA) formulation and a random search (RS) are also applied to the three scenarios to compare performances with NPGA. With 15 decision variables, the NPGA is demonstrated to outperform both the SGA algorithm and the RS by generating a better tradeoff curve. For example, for a given cost of $100,000, the NPGA solution found a design with 75% less mass remaining than the corresponding RS solution. In the 15-well scenario, the NPGA generated the full span of the Pareto optimal designs, but with 30% less computational effort than that required by the SGA. The RS failed to find any Pareto optimal solutions. The optimal population size for the NPGA was found by sensitivity analysis to be approximately 100, when the total computational cost was limited to 2000 function evaluations. The NPGA was found to be robust with respect to the other algorithm parameters (tournament size and niche radius) when using an optimal population size. The inclusion of niching produced better results in terms of covering the span of the tradeoff curve. As long as some niching was included, the results were insensitive to the value of the parameter that controls niching ( sigma sub(share) > 0). Researchers applied a multiobjective optimization algorithm to a problem in groundwater quality management involving remediation via pump-and-treat processes. The proposed multiobjective optimization approach utilizes the niched Pareto genetic algorithm (NPGA). The approach was used to simultaneously minimize the remedial design cost and the contaminant mass left over at completion of the remediation horizon. The study considered three test scenarios involving pumping rates for two-, five-, and 15-fixed-location wells. The three scenarios were also evaluated using a single objective genetic algorithm formulation and a random search. For the case involving 15 decision variables, the NPGA method outperformed both the single objective genetic algorithm and the random search. A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the (1) remedial design cost and (2) contaminant mass remaining at the end of the remediation horizon. Three test scenarios consider pumping rates for two-, five-, and 15 fixed-location wells as the decision variables. A single objective genetic algorithm (SGA) formulation and a random search (RS) are also applied to the three scenarios to compare performances with NPGA. With 15 decision variables, the NPGA is demonstrated to outperform both the SGA algorithm and the RS by generating a better tradeoff curve. For example, for a given cost of $100,000, the NPGA solution found a design with 75% less mass remaining than the corresponding RS solution. In the 15-well scenario, the NPGA generated the full span of the Pareto optimal designs, but with 30% less computational effort than that required by the SGA. The RS failed to find any Pareto optimal solutions. The optimal population size for the NPGA was found by sensitivity analysis to be approximately 100, when the total computational cost was limited to 2000 function evaluations. The NPGA was found to be robust with respect to the other algorithm parameters (tournament size and niche radius) when using an optimal population size. The inclusion of niching produced better results in terms of covering the span of the tradeoff curve. As long as some niching was included, the results were insensitive to the value of the parameter that controls niching ( σ share>0).
Author	Erickson, Mark Mayer, Alex Horn, Jeffrey
Author_xml	– sequence: 1 givenname: Mark surname: Erickson fullname: Erickson, Mark organization: Department of Geological Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan, USA – sequence: 2 givenname: Alex surname: Mayer fullname: Mayer, Alex email: asmayer@mtu.edu organization: Department of Geological Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan, USA – sequence: 3 givenname: Jeffrey surname: Horn fullname: Horn, Jeffrey organization: Department of Mathematics and Computer Science, Northern Michigan University, Marquette, Michigan, USA
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=13407360$$DView record in Pascal Francis
BookMark	eNqF0sFrFDEUBvAgFdxW_wQhF6U9jOZlMpkZPUgpWoWqBfUc3mTe7KbMJGuSrRT8453uFgUvcwqE3_cu33fMjnzwxNhzEK9AgH79TZSiLaAWzamAMyGEFEX5iK2gqWXR6qo-Yqu_5Ak7TulmRo2q5Yr9_rwbsytCd0M2u1viYZvdhCPvKbm152Hg6xh2vv-FmSKPNFHvMLvgebpLmab0huN2Ozp7-Jx93hD3zm6o59cYKQe-Jk_ZWY7jOkSXNxM__XJ9eX72lD0ecEz07OE9YT8-vP9-8bG4-nr56eL8qkDVqFwobLqmswidJrSgOwsWBts3siGoS9tqia3oKuyEAkWgOuyVBo1SIageyhP28nB3G8PPHaVsJpcsjSN6CrtkVNPWlZLVIpS1BCVLvQhBg2zKmS5CpYVQop3hiweIyeI4RPTWJbONcxvxzkCpRF1qMbvq4GwMKUUa_hFh7udg9nMw910bAWY_B1POubf_5azL-85yRDcupt8d0jTXdOsommQdeTuPIc7DMX1wCxf-AN9w0WQ
CODEN	AWREDI
CitedBy_id	crossref_primary_10_1007_s11269_012_0125_y crossref_primary_10_1016_j_jhydrol_2014_10_023 crossref_primary_10_1016_j_jhydrol_2022_127677 crossref_primary_10_1061__ASCE_WR_1943_5452_0001180 crossref_primary_10_1016_j_jenvman_2012_11_030 crossref_primary_10_3390_w13111574 crossref_primary_10_3389_fnins_2023_1251968 crossref_primary_10_1007_s12517_017_2996_y crossref_primary_10_1007_s10040_007_0200_2 crossref_primary_10_1016_j_envsoft_2012_02_002 crossref_primary_10_1016_j_energy_2016_10_035 crossref_primary_10_1016_j_neucom_2014_01_075 crossref_primary_10_1016_j_applthermaleng_2009_05_008 crossref_primary_10_1016_j_compchemeng_2005_04_005 crossref_primary_10_1061__ASCE_0733_9372_2007_133_8_809 crossref_primary_10_1016_j_eswa_2008_06_136 crossref_primary_10_1016_j_jenvman_2024_122699 crossref_primary_10_1016_j_envsoft_2004_11_012 crossref_primary_10_1016_S0309_1708_02_00054_4 crossref_primary_10_1016_j_jhydrol_2019_124498 crossref_primary_10_1109_TMAG_2017_2784401 crossref_primary_10_1007_s10040_012_0900_0 crossref_primary_10_1016_j_advwatres_2005_07_010 crossref_primary_10_1016_j_jconhyd_2009_11_004 crossref_primary_10_1007_s13201_022_01785_2 crossref_primary_10_1016_j_undsp_2023_11_009 crossref_primary_10_1061_JHTRBP_HZENG_1503 crossref_primary_10_1016_j_advwatres_2006_05_009 crossref_primary_10_1061__ASCE_HE_1943_5584_0000327 crossref_primary_10_1109_ACCESS_2024_3430970 crossref_primary_10_1002_nme_1432 crossref_primary_10_1016_j_envsoft_2007_02_001 crossref_primary_10_1111_j_1365_2664_2007_01367_x crossref_primary_10_1177_09544054221136512 crossref_primary_10_1080_09715010_2009_10514971 crossref_primary_10_1111_gwat_13098 crossref_primary_10_1016_j_advwatres_2007_02_008 crossref_primary_10_1002_2015WR017193 crossref_primary_10_1016_j_ijfatigue_2022_106840 crossref_primary_10_1016_j_jappgeo_2016_03_031 crossref_primary_10_1016_j_advwatres_2008_01_010 crossref_primary_10_2166_hydro_2023_059 crossref_primary_10_1061__ASCE_HE_1943_5584_0000198 crossref_primary_10_1016_j_envsoft_2017_05_004 crossref_primary_10_1007_s11269_012_0030_4 crossref_primary_10_1002_2014WR016825 crossref_primary_10_1007_s12303_010_0010_8 crossref_primary_10_1155_2014_539128 crossref_primary_10_1007_s11269_006_9109_0 crossref_primary_10_1016_j_jconhyd_2006_11_009 crossref_primary_10_1061__ASCE_HZ_2153_5515_0000304 crossref_primary_10_1016_j_jhydrol_2016_01_009 crossref_primary_10_1016_j_jclepro_2020_122897 crossref_primary_10_1016_j_advwatres_2006_06_006 crossref_primary_10_1080_02626667_2012_754103 crossref_primary_10_1061__ASCE_0733_9496_2005_131_1_45 crossref_primary_10_1016_j_asoc_2015_06_007 crossref_primary_10_2166_ws_2018_059 crossref_primary_10_1061__ASCE_WR_1943_5452_0000053 crossref_primary_10_1080_00207720802556252 crossref_primary_10_1016_j_jclepro_2022_132697 crossref_primary_10_1016_j_jhydrol_2013_03_022 crossref_primary_10_1007_s11269_022_03289_9 crossref_primary_10_1016_j_cageo_2006_09_002 crossref_primary_10_1016_j_camwa_2008_10_003 crossref_primary_10_1007_s00521_018_3491_4 crossref_primary_10_1016_j_envsoft_2005_12_021 crossref_primary_10_1016_j_scitotenv_2021_150811 crossref_primary_10_1007_s00170_005_0035_8 crossref_primary_10_1016_j_jconhyd_2023_104201 crossref_primary_10_1109_ACCESS_2019_2948057 crossref_primary_10_1016_j_jhydrol_2007_05_008 crossref_primary_10_2134_agronj2004_0631 crossref_primary_10_1007_s12303_009_0038_9 crossref_primary_10_1016_j_envsoft_2012_05_002 crossref_primary_10_1029_2005WR004436 crossref_primary_10_1080_0305215X_2010_491548 crossref_primary_10_1016_j_jenvman_2008_07_002 crossref_primary_10_1093_jcde_qwad110 crossref_primary_10_1007_s10040_019_01963_8 crossref_primary_10_1061__ASCE_1090_025X_2003_7_2_131 crossref_primary_10_1016_j_advwatres_2006_01_008 crossref_primary_10_1029_2008WR007108 crossref_primary_10_1016_j_jconhyd_2008_05_002 crossref_primary_10_3390_app13042064 crossref_primary_10_1002_hyp_11412 crossref_primary_10_1016_j_jestch_2017_05_005 crossref_primary_10_1007_s12665_013_2291_5 crossref_primary_10_1016_j_jmmm_2019_01_029 crossref_primary_10_1007_s10040_021_02383_3 crossref_primary_10_1111_j_1745_6592_2010_01287_x crossref_primary_10_1016_j_advwatres_2007_03_006 crossref_primary_10_1002_hyp_5036 crossref_primary_10_1111_j_1750_3841_2009_01348_x crossref_primary_10_1007_s00170_014_6240_6 crossref_primary_10_1080_07408170802322994 crossref_primary_10_1080_02626667_2010_512467 crossref_primary_10_1111_j_1745_6592_2011_01375_x crossref_primary_10_1007_s10040_004_0424_3 crossref_primary_10_1061__ASCE_HE_1943_5584_0000823 crossref_primary_10_1109_TMAG_2017_2702758 crossref_primary_10_1061__ASCE_HE_1943_5584_0001510 crossref_primary_10_1016_j_agwat_2010_01_013
Cites_doi	10.1029/WR018i004p00773 10.1029/95WR03528 10.1029/94WR02039 10.1029/97WR00366 10.1111/j.1745-6584.1999.tb01193.x 10.1029/97WR03605 10.1109/ICEC.1994.350037 10.1061/(ASCE)0733-9496(1999)125:2(76) 10.1002/j.1551-8833.1983.tb05177.x 10.1029/94WR02740 10.1061/(ASCE)0733-9496(2000)126:3(128) 10.1061/(ASCE)0733-9496(1995)121:2(171) 10.1029/WR020i004p00415 10.1029/91WR01468 10.1029/94WR00554 10.1029/93WR03511 10.1029/95RG00394 10.1109/3468.650319
ContentType	Journal Article
Copyright	2002 Elsevier Science Ltd 2002 INIST-CNRS
Copyright_xml	– notice: 2002 Elsevier Science Ltd – notice: 2002 INIST-CNRS
DBID	AAYXX CITATION IQODW 7ST C1K SOI 7QH 7TG 7TV 7UA KL. 7SU 8FD FR3 KR7 7S9 L.6
DOI	10.1016/S0309-1708(01)00020-3
DatabaseName	CrossRef Pascal-Francis Environment Abstracts Environmental Sciences and Pollution Management Environment Abstracts Aqualine Meteorological & Geoastrophysical Abstracts Pollution Abstracts Water Resources Abstracts Meteorological & Geoastrophysical Abstracts - Academic Environmental Engineering Abstracts Technology Research Database Engineering Research Database Civil Engineering Abstracts AGRICOLA AGRICOLA - Academic
DatabaseTitle	CrossRef Environment Abstracts Environmental Sciences and Pollution Management Meteorological & Geoastrophysical Abstracts Pollution Abstracts Aqualine Meteorological & Geoastrophysical Abstracts - Academic Water Resources Abstracts Civil Engineering Abstracts Engineering Research Database Technology Research Database Environmental Engineering Abstracts AGRICOLA AGRICOLA - Academic
DatabaseTitleList	Civil Engineering Abstracts Environment Abstracts Meteorological & Geoastrophysical Abstracts
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1872-9657
EndPage	65
ExternalDocumentID	308263510 13407360 10_1016_S0309_1708_01_00020_3 S0309170801000203
GroupedDBID	--K --M -~X .~1 0R~ 1B1 1RT 1~. 1~5 23M 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 8WZ 9JN A6W AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALCJ AALRI AAOAW AAQFI AAQXK AATLK AAXUO ABEFU ABFNM ABGRD ABMAC ABQEM ABQYD ABXDB ABYKQ ACDAQ ACGFS ACIWK ACLVX ACPRK ACRLP ACSBN ADBBV ADEZE ADMUD ADQTV AEBSH AEKER AENEX AFKWA AFRAH AFTJW AFXIZ AGHFR AGUBO AGYEJ AHHHB AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG ATOGT AVWKF AXJTR AZFZN BKOJK BLXMC CBWCG CS3 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HMA HVGLF HZ~ IHE IMUCA J1W KOM LY3 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SDF SDG SDP SEP SES SEW SPC SPCBC SSA SSE SSZ T5K TN5 WUQ XPP ZMT ~02 ~G- ~KM 9DU AAHBH AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD AGCQF AGRNS BNPGV IQODW SSH 7ST C1K SOI 7QH 7TG 7TV 7UA KL. 7SU 8FD FR3 KR7 7S9 L.6
ID	FETCH-LOGICAL-a484t-4a8b8bca1b6eac16bc1c1fcd828e173c962a90b5ab0414e14bad4616a24a14d13
ISICitedReferencesCount	120
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000173333400005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0309-1708
IngestDate	Thu Oct 02 07:04:54 EDT 2025 Tue Oct 07 09:45:43 EDT 2025 Tue Oct 07 09:36:28 EDT 2025 Tue Oct 07 09:17:26 EDT 2025 Mon Jul 21 09:16:00 EDT 2025 Tue Nov 18 22:01:32 EST 2025 Sat Nov 29 02:37:27 EST 2025 Fri Feb 23 02:33:01 EST 2024
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	algorithms sensitivity analysis plumes ground water pollution contamination pumping remediation hydraulic conductivity aquifers water quality optimization design water resource management wells
Language	English
License	https://www.elsevier.com/tdm/userlicense/1.0 CC BY 4.0
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-a484t-4a8b8bca1b6eac16bc1c1fcd828e173c962a90b5ab0414e14bad4616a24a14d13
Notes	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2
PQID	14600409
PQPubID	23462
PageCount	15
ParticipantIDs	proquest_miscellaneous_48975425 proquest_miscellaneous_27214236 proquest_miscellaneous_16128342 proquest_miscellaneous_14600409 pascalfrancis_primary_13407360 crossref_primary_10_1016_S0309_1708_01_00020_3 crossref_citationtrail_10_1016_S0309_1708_01_00020_3 elsevier_sciencedirect_doi_10_1016_S0309_1708_01_00020_3
PublicationCentury	2000
PublicationDate	2002 2002-1-00 20020101
PublicationDateYYYYMMDD	2002-01-01
PublicationDate_xml	– year: 2002 text: 2002
PublicationDecade	2000
PublicationPlace	Oxford
PublicationPlace_xml	– name: Oxford
PublicationTitle	Advances in water resources
PublicationYear	2002
Publisher	Elsevier Ltd Elsevier Science
Publisher_xml	– name: Elsevier Ltd – name: Elsevier Science
References	Horn J. The nature of niching: genetic algorithms and the evolution of optimal, cooperative populations. PhD thesis, University of Illinois at Urbana Champaign, Urbana, Illinois, 1997 Freeze, Gorelick (BIB7) 1999; 37 Huang, Mayer (BIB16) 1997; 33 LaBolle, Fogg, Tompson (BIB17) 1996; 32 Maxwell RM. Understanding the effects of uncertainty and variability on groundwater-driven health risk assessment. PhD dissertation, University of California, Berkeley, CA, 1998 Maxwell, Pelmulder, Tompson, Kastenburg (BIB19) 1998; 34 Means RS. Environmental remediation cost data – assemblies. 6th annual ed. R.S. Means Co. and Talisman Partners, Englewood, CO, 2000 Wagner BJ. Recent advances in simulation-optimization groundwater management modeling. Rev. Geophys. Supplement, US Natl. Rep. Int. Union Geod. Geophys., 1995;33:1021–8 Horn J, Nafpliotis N, Goldberg DE. A niched Pareto genetic algorithm for multiobjective optimization. In: Proceedings of the First IEEE Conference on Evolutionary Computation (ICEC `94), Piscataway, NJ: IEEE Service Center; 1994. p. 82–7 Sawyer, Ahlfeld, King (BIB25) 1995; 31 Goldberg, Richardson (BIB9) 1987 Horn J, Nafpliotis N. Multiobjective optimization using the niched Pareto genetic algorithm. Technical Report IlliGAl Report 93005, University of Illinois at Urbana-Champaign, Urbana, IL, 1993 Ritzel, Eheart, Ranjithan (BIB24) 1994; 30 Goldberg (BIB8) 1989 Hand (BIB12) 2000 Chan Hilton, Culver (BIB1) 2000; 126 Fetter CW. Contaminant hydrogeology. 2nd. ed. Upper Saddle River, NJ: Prentice Hall; 1999 Richardson JT, Palmer MR, Liepins G. Hilliard M. Some guidelines for genetic algorithms with penalty functions. In: Proceedings of the Third International Conference on Genetic Algorithms. San Mateo, CA: Morgan Kaufman; 1989. p. 191–7 McKinney, Lin (BIB21) 1994; 30 Cieniawski, Eheart, Ranjithan (BIB2) 1995; 31 Xiang, Sykes, Thomson (BIB27) 1995; 121 Dougherty, Marryott (BIB4) 1991; 27 Fonseca, Fleming (BIB6) 1998; 28 Gorelick, Voss, Gill, Murray, Saunders, Wright (BIB11) 1984; 20 Randke, Snoeyink (BIB23) 1983; 75 Das, Datta (BIB3) 1999; 125 Gorelick (BIB10) 1982; 18 Cieniawski (10.1016/S0309-1708(01)00020-3_BIB2) 1995; 31 Hand (10.1016/S0309-1708(01)00020-3_BIB12) 2000 Chan Hilton (10.1016/S0309-1708(01)00020-3_BIB1) 2000; 126 10.1016/S0309-1708(01)00020-3_BIB13 10.1016/S0309-1708(01)00020-3_BIB14 10.1016/S0309-1708(01)00020-3_BIB15 10.1016/S0309-1708(01)00020-3_BIB18 Gorelick (10.1016/S0309-1708(01)00020-3_BIB10) 1982; 18 McKinney (10.1016/S0309-1708(01)00020-3_BIB21) 1994; 30 10.1016/S0309-1708(01)00020-3_BIB5 Das (10.1016/S0309-1708(01)00020-3_BIB3) 1999; 125 Huang (10.1016/S0309-1708(01)00020-3_BIB16) 1997; 33 Dougherty (10.1016/S0309-1708(01)00020-3_BIB4) 1991; 27 Maxwell (10.1016/S0309-1708(01)00020-3_BIB19) 1998; 34 10.1016/S0309-1708(01)00020-3_BIB20 Ritzel (10.1016/S0309-1708(01)00020-3_BIB24) 1994; 30 10.1016/S0309-1708(01)00020-3_BIB22 LaBolle (10.1016/S0309-1708(01)00020-3_BIB17) 1996; 32 Xiang (10.1016/S0309-1708(01)00020-3_BIB27) 1995; 121 Goldberg (10.1016/S0309-1708(01)00020-3_BIB8) 1989 10.1016/S0309-1708(01)00020-3_BIB26 Goldberg (10.1016/S0309-1708(01)00020-3_BIB9) 1987 Gorelick (10.1016/S0309-1708(01)00020-3_BIB11) 1984; 20 Freeze (10.1016/S0309-1708(01)00020-3_BIB7) 1999; 37 Randke (10.1016/S0309-1708(01)00020-3_BIB23) 1983; 75 Fonseca (10.1016/S0309-1708(01)00020-3_BIB6) 1998; 28 Sawyer (10.1016/S0309-1708(01)00020-3_BIB25) 1995; 31
References_xml	– start-page: 41 year: 1987 end-page: 49 ident: BIB9 article-title: Genetic algorithms with sharing for multimodal function optimization publication-title: Genetic algorithms and their applications: proceedings of the second international conference on genetic algorithms – volume: 27 start-page: 2493 year: 1991 end-page: 2508 ident: BIB4 article-title: Optimal groundwater management, 1, simulated annealing publication-title: Water Resour. Res. – volume: 30 start-page: 1589 year: 1994 end-page: 1603 ident: BIB24 article-title: Using genetic algorithms to solve a multiple objective groundwater pollution containment problem publication-title: Water Resour. Res. – volume: 126 start-page: 128 year: 2000 end-page: 137 ident: BIB1 article-title: Constraint handling for genetic algorithms in optimal remediation design publication-title: J. Water Resour. Plan. Manage. – volume: 28 start-page: 26 year: 1998 end-page: 37 ident: BIB6 article-title: Multiobjective optimization and multiple constraint handling with evolutionary algorithms I: a unified formulation publication-title: IEEE Trans. Systems, Man, Cybernetics, Part A: Systems Humans – reference: Means RS. Environmental remediation cost data – assemblies. 6th annual ed. R.S. Means Co. and Talisman Partners, Englewood, CO, 2000 – volume: 18 start-page: 773 year: 1982 end-page: 781 ident: BIB10 article-title: A model for managing sources of groundwater pollution publication-title: Water Resour. Res. – volume: 75 start-page: 406 year: 1983 end-page: 418 ident: BIB23 article-title: Evaluating GAC adsorptive capacity publication-title: J. Amer. Water Works Assoc. – reference: Horn J, Nafpliotis N. Multiobjective optimization using the niched Pareto genetic algorithm. Technical Report IlliGAl Report 93005, University of Illinois at Urbana-Champaign, Urbana, IL, 1993 – volume: 37 start-page: 934 year: 1999 end-page: 954 ident: BIB7 article-title: Convergence of stochastic optimization and decision analysis in the engineering design of aquifer remediation publication-title: Ground Water – volume: 34 start-page: 833 year: 1998 end-page: 847 ident: BIB19 article-title: On the development of a new methodology for groundwater driven health risk assessment publication-title: Water Resour. Res. – volume: 31 start-page: 1373 year: 1995 end-page: 1385 ident: BIB25 article-title: Groundwater remediation design using a three-dimensional simulation model and mixed-integer programming publication-title: Water Resour. Res. – year: 2000 ident: BIB12 publication-title: Personal communication, Department of Civil and Environmental Engineering – reference: Richardson JT, Palmer MR, Liepins G. Hilliard M. Some guidelines for genetic algorithms with penalty functions. In: Proceedings of the Third International Conference on Genetic Algorithms. San Mateo, CA: Morgan Kaufman; 1989. p. 191–7 – volume: 31 start-page: 399 year: 1995 end-page: 409 ident: BIB2 article-title: Using genetic algorithms to solve a multiobjective groundwater monitoring problem publication-title: Water Resour. Res. – volume: 33 start-page: 1001 year: 1997 end-page: 1012 ident: BIB16 article-title: Pump-and-treat optimization using well locations and pumping rates as decision variables publication-title: Water Resour. Res. – year: 1989 ident: BIB8 publication-title: Genetic algorithms in search, optimization, and machine learning – reference: Horn J. The nature of niching: genetic algorithms and the evolution of optimal, cooperative populations. PhD thesis, University of Illinois at Urbana Champaign, Urbana, Illinois, 1997 – volume: 121 start-page: 171 year: 1995 end-page: 181 ident: BIB27 article-title: Alternative formulations for optimal groundwater remediation design publication-title: J. Water Resour. Plan. Manage. – reference: Maxwell RM. Understanding the effects of uncertainty and variability on groundwater-driven health risk assessment. PhD dissertation, University of California, Berkeley, CA, 1998 – reference: Fetter CW. Contaminant hydrogeology. 2nd. ed. Upper Saddle River, NJ: Prentice Hall; 1999 – reference: Horn J, Nafpliotis N, Goldberg DE. A niched Pareto genetic algorithm for multiobjective optimization. In: Proceedings of the First IEEE Conference on Evolutionary Computation (ICEC `94), Piscataway, NJ: IEEE Service Center; 1994. p. 82–7 – reference: Wagner BJ. Recent advances in simulation-optimization groundwater management modeling. Rev. Geophys. Supplement, US Natl. Rep. Int. Union Geod. Geophys., 1995;33:1021–8 – volume: 20 start-page: 415 year: 1984 end-page: 427 ident: BIB11 article-title: Aquifer reclamation design: the use of contaminant transport coupled with non-linear programming publication-title: Water Resour. Res. – volume: 125 start-page: 76 year: 1999 end-page: 87 ident: BIB3 article-title: Development of multiobjective management models for coastal aquifers publication-title: J. Water Resour. Plan. Manage. – volume: 30 start-page: 1897 year: 1994 end-page: 1906 ident: BIB21 article-title: Genetic algorithm solutions of groundwater management models publication-title: Water Resour. Res. – volume: 32 start-page: 583 year: 1996 end-page: 593 ident: BIB17 article-title: Random-walk simulation of transport in heterogeneous porous media: local mass-conservation problem and implementation methods publication-title: Water Resour. Res. – start-page: 41 year: 1987 ident: 10.1016/S0309-1708(01)00020-3_BIB9 article-title: Genetic algorithms with sharing for multimodal function optimization – year: 1989 ident: 10.1016/S0309-1708(01)00020-3_BIB8 – ident: 10.1016/S0309-1708(01)00020-3_BIB20 – ident: 10.1016/S0309-1708(01)00020-3_BIB18 – ident: 10.1016/S0309-1708(01)00020-3_BIB22 – volume: 18 start-page: 773 issue: 4 year: 1982 ident: 10.1016/S0309-1708(01)00020-3_BIB10 article-title: A model for managing sources of groundwater pollution publication-title: Water Resour. Res. doi: 10.1029/WR018i004p00773 – volume: 32 start-page: 583 issue: 3 year: 1996 ident: 10.1016/S0309-1708(01)00020-3_BIB17 article-title: Random-walk simulation of transport in heterogeneous porous media: local mass-conservation problem and implementation methods publication-title: Water Resour. Res. doi: 10.1029/95WR03528 – volume: 31 start-page: 399 issue: 2 year: 1995 ident: 10.1016/S0309-1708(01)00020-3_BIB2 article-title: Using genetic algorithms to solve a multiobjective groundwater monitoring problem publication-title: Water Resour. Res. doi: 10.1029/94WR02039 – volume: 33 start-page: 1001 issue: 5 year: 1997 ident: 10.1016/S0309-1708(01)00020-3_BIB16 article-title: Pump-and-treat optimization using well locations and pumping rates as decision variables publication-title: Water Resour. Res. doi: 10.1029/97WR00366 – ident: 10.1016/S0309-1708(01)00020-3_BIB14 – volume: 37 start-page: 934 issue: 6 year: 1999 ident: 10.1016/S0309-1708(01)00020-3_BIB7 article-title: Convergence of stochastic optimization and decision analysis in the engineering design of aquifer remediation publication-title: Ground Water doi: 10.1111/j.1745-6584.1999.tb01193.x – year: 2000 ident: 10.1016/S0309-1708(01)00020-3_BIB12 – volume: 34 start-page: 833 issue: 4 year: 1998 ident: 10.1016/S0309-1708(01)00020-3_BIB19 article-title: On the development of a new methodology for groundwater driven health risk assessment publication-title: Water Resour. Res. doi: 10.1029/97WR03605 – ident: 10.1016/S0309-1708(01)00020-3_BIB13 doi: 10.1109/ICEC.1994.350037 – volume: 125 start-page: 76 issue: 2 year: 1999 ident: 10.1016/S0309-1708(01)00020-3_BIB3 article-title: Development of multiobjective management models for coastal aquifers publication-title: J. Water Resour. Plan. Manage. doi: 10.1061/(ASCE)0733-9496(1999)125:2(76) – volume: 75 start-page: 406 issue: 8 year: 1983 ident: 10.1016/S0309-1708(01)00020-3_BIB23 article-title: Evaluating GAC adsorptive capacity publication-title: J. Amer. Water Works Assoc. doi: 10.1002/j.1551-8833.1983.tb05177.x – volume: 31 start-page: 1373 issue: 5 year: 1995 ident: 10.1016/S0309-1708(01)00020-3_BIB25 article-title: Groundwater remediation design using a three-dimensional simulation model and mixed-integer programming publication-title: Water Resour. Res. doi: 10.1029/94WR02740 – ident: 10.1016/S0309-1708(01)00020-3_BIB5 – volume: 126 start-page: 128 issue: 3 year: 2000 ident: 10.1016/S0309-1708(01)00020-3_BIB1 article-title: Constraint handling for genetic algorithms in optimal remediation design publication-title: J. Water Resour. Plan. Manage. doi: 10.1061/(ASCE)0733-9496(2000)126:3(128) – volume: 121 start-page: 171 issue: 2 year: 1995 ident: 10.1016/S0309-1708(01)00020-3_BIB27 article-title: Alternative formulations for optimal groundwater remediation design publication-title: J. Water Resour. Plan. Manage. doi: 10.1061/(ASCE)0733-9496(1995)121:2(171) – volume: 20 start-page: 415 year: 1984 ident: 10.1016/S0309-1708(01)00020-3_BIB11 article-title: Aquifer reclamation design: the use of contaminant transport coupled with non-linear programming publication-title: Water Resour. Res. doi: 10.1029/WR020i004p00415 – volume: 27 start-page: 2493 issue: 10 year: 1991 ident: 10.1016/S0309-1708(01)00020-3_BIB4 article-title: Optimal groundwater management, 1, simulated annealing publication-title: Water Resour. Res. doi: 10.1029/91WR01468 – volume: 30 start-page: 1897 issue: 6 year: 1994 ident: 10.1016/S0309-1708(01)00020-3_BIB21 article-title: Genetic algorithm solutions of groundwater management models publication-title: Water Resour. Res. doi: 10.1029/94WR00554 – volume: 30 start-page: 1589 issue: 5 year: 1994 ident: 10.1016/S0309-1708(01)00020-3_BIB24 article-title: Using genetic algorithms to solve a multiple objective groundwater pollution containment problem publication-title: Water Resour. Res. doi: 10.1029/93WR03511 – ident: 10.1016/S0309-1708(01)00020-3_BIB26 doi: 10.1029/95RG00394 – ident: 10.1016/S0309-1708(01)00020-3_BIB15 – volume: 28 start-page: 26 issue: 1 year: 1998 ident: 10.1016/S0309-1708(01)00020-3_BIB6 article-title: Multiobjective optimization and multiple constraint handling with evolutionary algorithms I: a unified formulation publication-title: IEEE Trans. Systems, Man, Cybernetics, Part A: Systems Humans doi: 10.1109/3468.650319
SSID	ssj0008472
Score	2.0518255
Snippet	A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The... Researchers applied a multiobjective optimization algorithm to a problem in groundwater quality management involving remediation via pump-and-treat processes....
SourceID	proquest pascalfrancis crossref elsevier
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	51
SubjectTerms	algorithms aquifers Computation Computational efficiency Contaminants Cost engineering Design engineering Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Exact sciences and technology Formulations Genetic algorithms groundwater contamination Groundwater remediation Hydrogeology Hydrology. Hydrogeology Mathematical models Pareto optimality pollution control Pollution, environment geology Pumping rates Remediation trichloroethylene water purification wells
Title	Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA)
URI	https://dx.doi.org/10.1016/S0309-1708(01)00020-3 https://www.proquest.com/docview/14600409 https://www.proquest.com/docview/16128342 https://www.proquest.com/docview/27214236 https://www.proquest.com/docview/48975425
Volume	25
WOSCitedRecordID	wos000173333400005&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-9657 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0008472 issn: 0309-1708 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Jb9NAFB6FlAMIIVYRljIHDq2QweMZ22NuUVWgINKqLVI5WeMZG4pSO0rS0gN_h__Jm8VLUoXAgYsVWTN-kd_nt8zbEHoRx0mQZ0J4LKPSA1AQT3fR8rKQ8zCSkSpCZYZNxKMRPzlJDnq9X3UtzMU4Lkt-eZlM_iur4R4wW5fO_gO7m4fCDfgNTIcrsB2uf8V4U1LrVdl3K8peViAUznQoxuRqaONQV3KU6ofQ_RH18aCy7HFdnU2OXCeuXWcRlDppVIHJOc3BXgXyuen1Ov5aTU_n387MWJ-Dd8P6aKHubGtzDEzWbU3RBgxaY_5wb-fj0f5ouXTo0_CLTdPQRTgN_PYPR50KtIVDi9a5beponOjqiDsd6yGxz7uy2RZFL2DQClrXpdaqbDtt4ooysOcSR82D4T3osQSJCb96tNWAddR_STE26YqEgttLI_8a2gjiMPH7aGO4t3vyoVH5oOKbcJWm1JaKvW7Jb_lk25FeZQTdmogZfJqFnalyxTwwNs_xHXTbOSt4aEF2F_Xy8h662WlheR_9XIIbdnDDFm64KnAHbrgDN-zg9gZ3wKbXA9iwBRu2YMMObLgBG97SUNt-gD6_3T3eee-5iR6eYJzNPSZ4xjMpSBaBwidRJokkhVTg9uckpjKJApH4WSgynxGWE5YJxSISiYAJwhShD1G_rMr8EcIFI1ySUDHBKOOFL2LKlJ-rMJEBbFYDxOpXnErX7l5PXRmnbV4jcCbVnEl9khrOpHSAXjXbJrbfy7oNvOZf6oxWa4ymAMN1WzcX-N0SdHgboOc1AFKQ-jqUJ8q8Op9ph12r3-QPK8B14ZQFq1cEsW63SKPVKxhP9IDs8PG6P_oE3TBTkszR5FPUn0_P82fouryYn86mm-5r-Q01Aewy
linkProvider	Elsevier
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=Multi-objective+optimal+design+of+groundwater+remediation+systems%3A+application+of+the+niched+Pareto+genetic+algorithm+%28NPGA%29&rft.jtitle=Advances+in+water+resources&rft.au=ERICKSON%2C+Mark&rft.au=MAYER%2C+Alex&rft.au=HORN%2C+Jeffrey&rft.date=2002&rft.pub=Elsevier+Science&rft.issn=0309-1708&rft.volume=25&rft.issue=1&rft.spage=51&rft.epage=65&rft_id=info:doi/10.1016%2FS0309-1708%2801%2900020-3&rft.externalDBID=n%2Fa&rft.externalDocID=13407360
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0309-1708&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0309-1708&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0309-1708&client=summon