Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach
Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimizati...
Gespeichert in:
| Veröffentlicht in: | Water resources management 2006-04, Vol.20 (2), p.227-255 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 255 |
|---|---|
| container_issue | 2 |
| container_start_page | 227 |
| container_title | Water resources management |
| container_volume | 20 |
| creator | Reis, L.F.R Bessler, F.T Walters, G.A Savic, D |
| description | Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form. |
| doi_str_mv | 10.1007/s11269-006-8049-z |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_743636567</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>19280450</sourcerecordid><originalsourceid>FETCH-LOGICAL-c455t-d9d12f0a0b7d9ed03f8e6a1eae39db30606d85e754357dddc1bef88466534f063</originalsourceid><addsrcrecordid>eNp9kU2LFDEQhoMoOK7-AE8Gwa9DtNL56hyHQUdhYBfXxWNId6pne-nutEmPMPvrzTALggdPOdTzVqXqIeQlh48cwHzKnFfaMgDNapCW3T8iK66MYFwreExWYCtg0kj-lDzL-Q6gpCysSPjpF0z0-jDPw5F-x4zpd-wTvZwx-aWPE22OdBPHpp8w0C1OuPQtXQ_7mPrldqSM7krFJ3qV4j75ceynPX2_XbPd1Qe6nucUfXv7nDzp_JDxxcN7QW6-fP6x-cp2l9tvm_WOtVKphQUbeNWBh8YEiwFEV6P2HD0KGxoBGnSoFRolhTIhhJY32NW11FoJ2YEWF-TduW8Z--uAeXFjn1scBj9hPGRnpNBCK20K-fa_JLdVOaOCAr7-B7yLhzSVLZxRFWgtjC0QP0Ntijkn7Nyc-tGno-PgTnrcWY8retxJj7svmTcPjX1u_dAlP7V9_hs0Bspip5--OnOdj87vU2Furivgohi0qpaV-AOmI5fh</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>752066379</pqid></control><display><type>article</type><title>Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach</title><source>SpringerLink Journals - AutoHoldings</source><creator>Reis, L.F.R ; Bessler, F.T ; Walters, G.A ; Savic, D</creator><creatorcontrib>Reis, L.F.R ; Bessler, F.T ; Walters, G.A ; Savic, D</creatorcontrib><description>Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form.</description><identifier>ISSN: 0920-4741</identifier><identifier>EISSN: 1573-1650</identifier><identifier>DOI: 10.1007/s11269-006-8049-z</identifier><identifier>CODEN: WRMAEJ</identifier><language>eng</language><publisher>Dordrecht: Springer</publisher><subject>Algorithms ; Earth sciences ; Earth, ocean, space ; Exact sciences and technology ; Genetic algorithms ; Hydrology. Hydrogeology ; Imports ; Linear programming ; Operations research ; Reservoir operation ; Studies ; Water conveyance ; Water resources ; Water supply</subject><ispartof>Water resources management, 2006-04, Vol.20 (2), p.227-255</ispartof><rights>2006 INIST-CNRS</rights><rights>Springer Science + Business Media, Inc. 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-d9d12f0a0b7d9ed03f8e6a1eae39db30606d85e754357dddc1bef88466534f063</citedby><cites>FETCH-LOGICAL-c455t-d9d12f0a0b7d9ed03f8e6a1eae39db30606d85e754357dddc1bef88466534f063</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17704667$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Reis, L.F.R</creatorcontrib><creatorcontrib>Bessler, F.T</creatorcontrib><creatorcontrib>Walters, G.A</creatorcontrib><creatorcontrib>Savic, D</creatorcontrib><title>Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach</title><title>Water resources management</title><description>Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form.</description><subject>Algorithms</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Genetic algorithms</subject><subject>Hydrology. Hydrogeology</subject><subject>Imports</subject><subject>Linear programming</subject><subject>Operations research</subject><subject>Reservoir operation</subject><subject>Studies</subject><subject>Water conveyance</subject><subject>Water resources</subject><subject>Water supply</subject><issn>0920-4741</issn><issn>1573-1650</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kU2LFDEQhoMoOK7-AE8Gwa9DtNL56hyHQUdhYBfXxWNId6pne-nutEmPMPvrzTALggdPOdTzVqXqIeQlh48cwHzKnFfaMgDNapCW3T8iK66MYFwreExWYCtg0kj-lDzL-Q6gpCysSPjpF0z0-jDPw5F-x4zpd-wTvZwx-aWPE22OdBPHpp8w0C1OuPQtXQ_7mPrldqSM7krFJ3qV4j75ceynPX2_XbPd1Qe6nucUfXv7nDzp_JDxxcN7QW6-fP6x-cp2l9tvm_WOtVKphQUbeNWBh8YEiwFEV6P2HD0KGxoBGnSoFRolhTIhhJY32NW11FoJ2YEWF-TduW8Z--uAeXFjn1scBj9hPGRnpNBCK20K-fa_JLdVOaOCAr7-B7yLhzSVLZxRFWgtjC0QP0Ntijkn7Nyc-tGno-PgTnrcWY8retxJj7svmTcPjX1u_dAlP7V9_hs0Bspip5--OnOdj87vU2Furivgohi0qpaV-AOmI5fh</recordid><startdate>20060401</startdate><enddate>20060401</enddate><creator>Reis, L.F.R</creator><creator>Bessler, F.T</creator><creator>Walters, G.A</creator><creator>Savic, D</creator><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7QH</scope><scope>7ST</scope><scope>7UA</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>H97</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>KR7</scope><scope>L.-</scope><scope>L.0</scope><scope>L.G</scope><scope>L6V</scope><scope>LK8</scope><scope>M0C</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>H96</scope></search><sort><creationdate>20060401</creationdate><title>Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach</title><author>Reis, L.F.R ; Bessler, F.T ; Walters, G.A ; Savic, D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-d9d12f0a0b7d9ed03f8e6a1eae39db30606d85e754357dddc1bef88466534f063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Algorithms</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>Genetic algorithms</topic><topic>Hydrology. Hydrogeology</topic><topic>Imports</topic><topic>Linear programming</topic><topic>Operations research</topic><topic>Reservoir operation</topic><topic>Studies</topic><topic>Water conveyance</topic><topic>Water resources</topic><topic>Water supply</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reis, L.F.R</creatorcontrib><creatorcontrib>Bessler, F.T</creatorcontrib><creatorcontrib>Walters, G.A</creatorcontrib><creatorcontrib>Savic, D</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>ABI/INFORM Global</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><jtitle>Water resources management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reis, L.F.R</au><au>Bessler, F.T</au><au>Walters, G.A</au><au>Savic, D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach</atitle><jtitle>Water resources management</jtitle><date>2006-04-01</date><risdate>2006</risdate><volume>20</volume><issue>2</issue><spage>227</spage><epage>255</epage><pages>227-255</pages><issn>0920-4741</issn><eissn>1573-1650</eissn><coden>WRMAEJ</coden><abstract>Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form.</abstract><cop>Dordrecht</cop><pub>Springer</pub><doi>10.1007/s11269-006-8049-z</doi><tpages>29</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0920-4741 |
| ispartof | Water resources management, 2006-04, Vol.20 (2), p.227-255 |
| issn | 0920-4741 1573-1650 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_743636567 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Algorithms Earth sciences Earth, ocean, space Exact sciences and technology Genetic algorithms Hydrology. Hydrogeology Imports Linear programming Operations research Reservoir operation Studies Water conveyance Water resources Water supply |
| title | Water Supply Reservoir Operation by Combined Genetic Algorithm - Linear Programming (GA-LP) Approach |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T20%3A35%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Water%20Supply%20Reservoir%20Operation%20by%20Combined%20Genetic%20Algorithm%20-%20Linear%20Programming%20(GA-LP)%20Approach&rft.jtitle=Water%20resources%20management&rft.au=Reis,%20L.F.R&rft.date=2006-04-01&rft.volume=20&rft.issue=2&rft.spage=227&rft.epage=255&rft.pages=227-255&rft.issn=0920-4741&rft.eissn=1573-1650&rft.coden=WRMAEJ&rft_id=info:doi/10.1007/s11269-006-8049-z&rft_dat=%3Cproquest_cross%3E19280450%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=752066379&rft_id=info:pmid/&rfr_iscdi=true |