Intelligent system for selection of order picking technologies
The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a righ...
Gespeichert in:
| Veröffentlicht in: | Wireless networks 2020-11, Vol.26 (8), p.5809-5816 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 5816 |
|---|---|
| container_issue | 8 |
| container_start_page | 5809 |
| container_title | Wireless networks |
| container_volume | 26 |
| creator | Villarreal-Zapata, Gabriela Salais-Fierro, Tomas E. Saucedo-Martínez, Jania Astrid |
| description | The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a right way. The purpose of this paper is to create an intelligent decision model to select the most appropriate order picking technology. The present study shows an artificial neural network (ANN) trained with the results of an analytic hierarchy process (AHP). The weighting of the determining criteria and the prioritization of the different technologies from several experts are obtained through the AHP, while the artificial neural network is used to automate the decision process. The designed ANN can synthesize expert judgments and then predict the prioritization of order picking technologies. |
| doi_str_mv | 10.1007/s11276-020-02262-x |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2449450943</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2449450943</sourcerecordid><originalsourceid>FETCH-LOGICAL-c367t-14004f4aa15ba517e397e7df3b906f8cc2b69a24d0be494437d84568ad62e1613</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKt_wNOC59XJxyabiyBFa6HgRc9hP2bXrdukJim0_97oCt48DDMM7zMDDyHXFG4pgLoLlDIlc2CQikmWH07IjBaK5SXV8jTNaZ0D8PKcXISwAYCSaz0j9ysbcRyHHm3MwjFE3Gad81nAEZs4OJu5LnO-RZ_thuZjsH0WsXm3bnT9gOGSnHXVGPDqt8_J29Pj6-I5X78sV4uHdd5wqWJOBYDoRFXRoq4KqpBrharteK1BdmXTsFrqiokWahRaCK7aUhSyrFrJkErK5-Rmurvz7nOPIZqN23ubXhomElGAFjyl2JRqvAvBY2d2fthW_mgomG9PZvJkkifz48kcEsQnKKSw7dH_nf6H-gKKBGsa</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2449450943</pqid></control><display><type>article</type><title>Intelligent system for selection of order picking technologies</title><source>SpringerLink Journals - AutoHoldings</source><creator>Villarreal-Zapata, Gabriela ; Salais-Fierro, Tomas E. ; Saucedo-Martínez, Jania Astrid</creator><creatorcontrib>Villarreal-Zapata, Gabriela ; Salais-Fierro, Tomas E. ; Saucedo-Martínez, Jania Astrid</creatorcontrib><description>The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a right way. The purpose of this paper is to create an intelligent decision model to select the most appropriate order picking technology. The present study shows an artificial neural network (ANN) trained with the results of an analytic hierarchy process (AHP). The weighting of the determining criteria and the prioritization of the different technologies from several experts are obtained through the AHP, while the artificial neural network is used to automate the decision process. The designed ANN can synthesize expert judgments and then predict the prioritization of order picking technologies.</description><identifier>ISSN: 1022-0038</identifier><identifier>EISSN: 1572-8196</identifier><identifier>DOI: 10.1007/s11276-020-02262-x</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Analytic hierarchy process ; Artificial neural networks ; Communications Engineering ; Computer Communication Networks ; Electrical Engineering ; Engineering ; IT in Business ; Materials handling ; Networks ; Neural networks ; Order picking ; Wireless networks</subject><ispartof>Wireless networks, 2020-11, Vol.26 (8), p.5809-5816</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020</rights><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-14004f4aa15ba517e397e7df3b906f8cc2b69a24d0be494437d84568ad62e1613</citedby><cites>FETCH-LOGICAL-c367t-14004f4aa15ba517e397e7df3b906f8cc2b69a24d0be494437d84568ad62e1613</cites><orcidid>0000-0002-5917-887X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11276-020-02262-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11276-020-02262-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Villarreal-Zapata, Gabriela</creatorcontrib><creatorcontrib>Salais-Fierro, Tomas E.</creatorcontrib><creatorcontrib>Saucedo-Martínez, Jania Astrid</creatorcontrib><title>Intelligent system for selection of order picking technologies</title><title>Wireless networks</title><addtitle>Wireless Netw</addtitle><description>The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a right way. The purpose of this paper is to create an intelligent decision model to select the most appropriate order picking technology. The present study shows an artificial neural network (ANN) trained with the results of an analytic hierarchy process (AHP). The weighting of the determining criteria and the prioritization of the different technologies from several experts are obtained through the AHP, while the artificial neural network is used to automate the decision process. The designed ANN can synthesize expert judgments and then predict the prioritization of order picking technologies.</description><subject>Analytic hierarchy process</subject><subject>Artificial neural networks</subject><subject>Communications Engineering</subject><subject>Computer Communication Networks</subject><subject>Electrical Engineering</subject><subject>Engineering</subject><subject>IT in Business</subject><subject>Materials handling</subject><subject>Networks</subject><subject>Neural networks</subject><subject>Order picking</subject><subject>Wireless networks</subject><issn>1022-0038</issn><issn>1572-8196</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1LAzEQhoMoWKt_wNOC59XJxyabiyBFa6HgRc9hP2bXrdukJim0_97oCt48DDMM7zMDDyHXFG4pgLoLlDIlc2CQikmWH07IjBaK5SXV8jTNaZ0D8PKcXISwAYCSaz0j9ysbcRyHHm3MwjFE3Gad81nAEZs4OJu5LnO-RZ_thuZjsH0WsXm3bnT9gOGSnHXVGPDqt8_J29Pj6-I5X78sV4uHdd5wqWJOBYDoRFXRoq4KqpBrharteK1BdmXTsFrqiokWahRaCK7aUhSyrFrJkErK5-Rmurvz7nOPIZqN23ubXhomElGAFjyl2JRqvAvBY2d2fthW_mgomG9PZvJkkifz48kcEsQnKKSw7dH_nf6H-gKKBGsa</recordid><startdate>20201101</startdate><enddate>20201101</enddate><creator>Villarreal-Zapata, Gabriela</creator><creator>Salais-Fierro, Tomas E.</creator><creator>Saucedo-Martínez, Jania Astrid</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-5917-887X</orcidid></search><sort><creationdate>20201101</creationdate><title>Intelligent system for selection of order picking technologies</title><author>Villarreal-Zapata, Gabriela ; Salais-Fierro, Tomas E. ; Saucedo-Martínez, Jania Astrid</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-14004f4aa15ba517e397e7df3b906f8cc2b69a24d0be494437d84568ad62e1613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analytic hierarchy process</topic><topic>Artificial neural networks</topic><topic>Communications Engineering</topic><topic>Computer Communication Networks</topic><topic>Electrical Engineering</topic><topic>Engineering</topic><topic>IT in Business</topic><topic>Materials handling</topic><topic>Networks</topic><topic>Neural networks</topic><topic>Order picking</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Villarreal-Zapata, Gabriela</creatorcontrib><creatorcontrib>Salais-Fierro, Tomas E.</creatorcontrib><creatorcontrib>Saucedo-Martínez, Jania Astrid</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications 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>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</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>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Wireless networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Villarreal-Zapata, Gabriela</au><au>Salais-Fierro, Tomas E.</au><au>Saucedo-Martínez, Jania Astrid</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intelligent system for selection of order picking technologies</atitle><jtitle>Wireless networks</jtitle><stitle>Wireless Netw</stitle><date>2020-11-01</date><risdate>2020</risdate><volume>26</volume><issue>8</issue><spage>5809</spage><epage>5816</epage><pages>5809-5816</pages><issn>1022-0038</issn><eissn>1572-8196</eissn><abstract>The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a right way. The purpose of this paper is to create an intelligent decision model to select the most appropriate order picking technology. The present study shows an artificial neural network (ANN) trained with the results of an analytic hierarchy process (AHP). The weighting of the determining criteria and the prioritization of the different technologies from several experts are obtained through the AHP, while the artificial neural network is used to automate the decision process. The designed ANN can synthesize expert judgments and then predict the prioritization of order picking technologies.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11276-020-02262-x</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-5917-887X</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1022-0038 |
| ispartof | Wireless networks, 2020-11, Vol.26 (8), p.5809-5816 |
| issn | 1022-0038 1572-8196 |
| language | eng |
| recordid | cdi_proquest_journals_2449450943 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Analytic hierarchy process Artificial neural networks Communications Engineering Computer Communication Networks Electrical Engineering Engineering IT in Business Materials handling Networks Neural networks Order picking Wireless networks |
| title | Intelligent system for selection of order picking technologies |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T04%3A58%3A08IST&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=Intelligent%20system%20for%20selection%20of%20order%20picking%20technologies&rft.jtitle=Wireless%20networks&rft.au=Villarreal-Zapata,%20Gabriela&rft.date=2020-11-01&rft.volume=26&rft.issue=8&rft.spage=5809&rft.epage=5816&rft.pages=5809-5816&rft.issn=1022-0038&rft.eissn=1572-8196&rft_id=info:doi/10.1007/s11276-020-02262-x&rft_dat=%3Cproquest_cross%3E2449450943%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=2449450943&rft_id=info:pmid/&rfr_iscdi=true |