Hybrid optimization enabled multi‐aggregator‐based charge scheduling of electric vehicle in internet of electric vehicles
Summary In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for the power system. The electric vehicle charge scheduling process is vital to encourage the daily usage of the electric vehicle. However, irregu...
Saved in:
| Published in: | Concurrency and computation Vol. 35; no. 9 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Hoboken, USA
John Wiley & Sons, Inc
25.04.2023
Wiley Subscription Services, Inc |
| Subjects: | |
| ISSN: | 1532-0626, 1532-0634 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Summary
In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for the power system. The electric vehicle charge scheduling process is vital to encourage the daily usage of the electric vehicle. However, irregular charging methods for electric vehicles may disturb voltage security areas because of their stochastic characteristics. Moreover, an electric vehicle requires recurrent charging owing to its constrained battery capacity, but it is a time‐consuming process. In this article, an effective charge scheduling model is devised using the fractional social sea lion optimization (Fr‐SSLO) algorithm. At first, IoEV network is simulated along with charge station and electric vehicle location. Furthermore, multi aggregator‐based charge scheduling is done for increasing the profit and amount of scheduled electric vehicles. Then, routing is performed based on developed Fr‐SSLO algorithm. Moreover, several fitness measures, including distance, energy and variable energy purchase are included. Here, the devised Fr‐SSLO model is designed by integrating fractional calculus (FC) and sea lion optimization (SLnO) technique along with SOA. After the completion of routing process, charge scheduling is performed based on developed Fr‐SSLO approach. Moreover, various fitness functions are also considered for computing better performance. |
|---|---|
| AbstractList | Summary
In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for the power system. The electric vehicle charge scheduling process is vital to encourage the daily usage of the electric vehicle. However, irregular charging methods for electric vehicles may disturb voltage security areas because of their stochastic characteristics. Moreover, an electric vehicle requires recurrent charging owing to its constrained battery capacity, but it is a time‐consuming process. In this article, an effective charge scheduling model is devised using the fractional social sea lion optimization (Fr‐SSLO) algorithm. At first, IoEV network is simulated along with charge station and electric vehicle location. Furthermore, multi aggregator‐based charge scheduling is done for increasing the profit and amount of scheduled electric vehicles. Then, routing is performed based on developed Fr‐SSLO algorithm. Moreover, several fitness measures, including distance, energy and variable energy purchase are included. Here, the devised Fr‐SSLO model is designed by integrating fractional calculus (FC) and sea lion optimization (SLnO) technique along with SOA. After the completion of routing process, charge scheduling is performed based on developed Fr‐SSLO approach. Moreover, various fitness functions are also considered for computing better performance. In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for the power system. The electric vehicle charge scheduling process is vital to encourage the daily usage of the electric vehicle. However, irregular charging methods for electric vehicles may disturb voltage security areas because of their stochastic characteristics. Moreover, an electric vehicle requires recurrent charging owing to its constrained battery capacity, but it is a time‐consuming process. In this article, an effective charge scheduling model is devised using the fractional social sea lion optimization (Fr‐SSLO) algorithm. At first, IoEV network is simulated along with charge station and electric vehicle location. Furthermore, multi aggregator‐based charge scheduling is done for increasing the profit and amount of scheduled electric vehicles. Then, routing is performed based on developed Fr‐SSLO algorithm. Moreover, several fitness measures, including distance, energy and variable energy purchase are included. Here, the devised Fr‐SSLO model is designed by integrating fractional calculus (FC) and sea lion optimization (SLnO) technique along with SOA. After the completion of routing process, charge scheduling is performed based on developed Fr‐SSLO approach. Moreover, various fitness functions are also considered for computing better performance. |
| Author | Suresh, Pandian Belsam Jeba Ananth, Manasea Selvin Ramya, Ganesan Shobana, Selvaraj |
| Author_xml | – sequence: 1 givenname: Pandian orcidid: 0000-0002-9725-2452 surname: Suresh fullname: Suresh, Pandian email: psuresh.ee1@gmail.com organization: St. Joseph College of Engineering, Sriperumbudur – sequence: 2 givenname: Selvaraj orcidid: 0000-0002-9403-5866 surname: Shobana fullname: Shobana, Selvaraj organization: Prathyusha Engineering College – sequence: 3 givenname: Ganesan surname: Ramya fullname: Ramya, Ganesan organization: SRM Institute of Science And Technology, Ramapuram Campus – sequence: 4 givenname: Manasea Selvin surname: Belsam Jeba Ananth fullname: Belsam Jeba Ananth, Manasea Selvin organization: SRM Institute of Science and Technology, Kattankulathur |
| BookMark | eNp1kNtKw0AQhhepYFsFHyHgjTepe8jxUkq1QkEv9DrsYZJu2SZxd6NUEHwEn9EnMW3FC6kwMDP83z8D_wgN6qYGhM4JnhCM6ZVsYZImcXSEhiRmNMQJiwa_M01O0Mi5FcaEYEaG6H2-EVaroGm9Xus37nVTB1BzYUAF6854_fXxyavKQsV9Y_tFcNdLcsltBYGTS1Cd0XUVNGUABqS3WgYvsNTSQKDrvjzYGvwh3Z2i45IbB2c_fYyebmaP03m4uL-9m14vQklzFoVKYsU5i0UJEWSM5DKDKAUqKFOEgxJRDoIBqDwVSSLjuIwoZUmecMXKFEo2Rhf7u61tnjtwvlg1na37lwVNs5zEWU6TnprsKWkb5yyUhdR-l4i3XJuC4GIbcdFHXGwj7g2Xfwyt1WtuN4fQcI--agObf7li-jDb8d-ZtZIP |
| CitedBy_id | crossref_primary_10_1007_s00521_024_09530_3 |
| Cites_doi | 10.1016/j.epsr.2016.09.018 10.1109/TII.2017.2778762 10.1002/jnm.2764 10.1016/j.omega.2016.04.005 10.1016/j.epsr.2017.02.019 10.1007/978-3-319-74461-2_3 10.1093/comjnl/bxz164 10.1007/s11276-020-02352-w 10.1016/j.energy.2019.02.184 10.1109/TTE.2017.2753403 10.1016/j.asoc.2018.07.008 10.1093/comjnl/bxaa173 10.1109/TIA.2020.3017563 10.1016/j.apenergy.2016.05.034 10.1155/2014/396529 10.1109/TSG.2012.2217761 10.46253/jcmps.v4i1.a5 10.1109/JIOT.2018.2876004 10.1016/j.egypro.2017.12.641 10.1016/j.egypro.2015.07.667 10.1016/j.rser.2014.12.036 10.1109/TSG.2011.2151888 10.1109/COMST.2016.2518628 10.1109/TIA.2020.2990096 10.1109/TSG.2020.3000850 10.1109/ICPADS.2011.42 10.1002/2050-7038.12593 10.1109/TITS.2018.2876287 10.1109/TSG.2018.2817067 10.1016/j.scs.2021.102820 |
| ContentType | Journal Article |
| Copyright | 2023 John Wiley & Sons, Ltd. |
| Copyright_xml | – notice: 2023 John Wiley & Sons, Ltd. |
| DBID | AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D |
| DOI | 10.1002/cpe.7654 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | CrossRef Computer and Information Systems Abstracts |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1532-0634 |
| EndPage | n/a |
| ExternalDocumentID | 10_1002_cpe_7654 CPE7654 |
| Genre | article |
| GroupedDBID | .3N .DC .GA 05W 0R~ 10A 1L6 1OC 33P 3SF 3WU 4.4 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 5GY 5VS 66C 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A03 AAESR AAEVG AAHHS AAHQN AAMNL AANLZ AAONW AAXRX AAYCA AAZKR ABCQN ABCUV ABEML ABIJN ACAHQ ACCFJ ACCZN ACPOU ACSCC ACXBN ACXQS ADBBV ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN ADZOD AEEZP AEIGN AEIMD AEQDE AEUQT AEUYR AFBPY AFFPM AFGKR AFPWT AFWVQ AHBTC AITYG AIURR AIWBW AJBDE AJXKR ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ATUGU AUFTA AZBYB BAFTC BDRZF BFHJK BHBCM BMNLL BROTX BRXPI BY8 CS3 D-E D-F DCZOG DPXWK DR2 DRFUL DRSTM EBS F00 F01 F04 F5P G-S G.N GNP GODZA HGLYW HHY HZ~ IX1 JPC KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A O66 O9- OIG P2W P2X P4D PQQKQ Q.N Q11 QB0 QRW R.K ROL RWI RX1 SUPJJ TN5 UB1 V2E W8V W99 WBKPD WIH WIK WOHZO WQJ WRC WXSBR WYISQ WZISG XG1 XV2 ~IA ~WT AAYXX ADMLS AEYWJ AGHNM AGYGG CITATION O8X 7SC 8FD JQ2 L7M L~C L~D |
| ID | FETCH-LOGICAL-c2934-dc0daa35bfe4e8319c8e47e2b23d1aedb49eb3eed97b66c55f4223696ad3f7ef3 |
| IEDL.DBID | DRFUL |
| ISICitedReferencesCount | 4 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000937575600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1532-0626 |
| IngestDate | Sun Nov 09 07:03:18 EST 2025 Sat Nov 29 03:49:53 EST 2025 Tue Nov 18 22:27:28 EST 2025 Wed Jan 22 16:22:50 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c2934-dc0daa35bfe4e8319c8e47e2b23d1aedb49eb3eed97b66c55f4223696ad3f7ef3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-9403-5866 0000-0002-9725-2452 |
| PQID | 2789158926 |
| PQPubID | 2045170 |
| PageCount | 20 |
| ParticipantIDs | proquest_journals_2789158926 crossref_citationtrail_10_1002_cpe_7654 crossref_primary_10_1002_cpe_7654 wiley_primary_10_1002_cpe_7654_CPE7654 |
| PublicationCentury | 2000 |
| PublicationDate | 25 April 2023 |
| PublicationDateYYYYMMDD | 2023-04-25 |
| PublicationDate_xml | – month: 04 year: 2023 text: 25 April 2023 day: 25 |
| PublicationDecade | 2020 |
| PublicationPlace | Hoboken, USA |
| PublicationPlace_xml | – name: Hoboken, USA – name: Hoboken |
| PublicationTitle | Concurrency and computation |
| PublicationYear | 2023 |
| Publisher | John Wiley & Sons, Inc Wiley Subscription Services, Inc |
| Publisher_xml | – name: John Wiley & Sons, Inc – name: Wiley Subscription Services, Inc |
| References | 2021; 69 2021; 4 2017; 4 2020; 63 2015; 73 2019; 10 2017; 67 2020; 56 2022; 21 2022; 65 2020; 33 2020; 11 2016; 18 2018; 20 2013; 9 2018; 6 2012; 3 2017; 14 2020; 30 2015; 44 2018 2016; 177 2020; 26 2017; 142 2014 2017; 143 2018; 71 2018; 10 2017; 147 2019; 175 e_1_2_9_30_1 e_1_2_9_31_1 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_10_1 e_1_2_9_13_1 e_1_2_9_32_1 e_1_2_9_33_1 Masadeh R (e_1_2_9_35_1) 2019; 10 e_1_2_9_15_1 e_1_2_9_14_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_16_1 e_1_2_9_19_1 e_1_2_9_20_1 Xu S (e_1_2_9_21_1) 2013; 9 e_1_2_9_22_1 e_1_2_9_24_1 e_1_2_9_23_1 e_1_2_9_8_1 e_1_2_9_7_1 Poier T (e_1_2_9_12_1) 2022; 21 e_1_2_9_6_1 e_1_2_9_5_1 e_1_2_9_4_1 e_1_2_9_3_1 e_1_2_9_2_1 Susan Augustine A (e_1_2_9_18_1) 2020; 33 e_1_2_9_9_1 e_1_2_9_26_1 e_1_2_9_25_1 e_1_2_9_28_1 e_1_2_9_27_1 e_1_2_9_29_1 |
| References_xml | – volume: 10 issue: 5 year: 2019 article-title: Sea lion optimization algorithm publication-title: Int J Adv Comput Sci Appl – start-page: 28 year: 2018 end-page: 36 – volume: 69 year: 2021 article-title: Intelligent charge scheduling and eco‐routing mechanism for electric vehicles: a multi‐objective heuristic approach publication-title: Sustain Cities Soc – volume: 56 start-page: 5811 issue: 5 year: 2020 end-page: 5823 article-title: Optimal electric vehicle charging strategy with Markov decision process and reinforcement learning technique publication-title: IEEE Trans Ind Appl – volume: 30 issue: 11 year: 2020 article-title: Social optimization algorithm with application to economic dispatch problem publication-title: Int Trans Electr Energy Syst – volume: 9 year: 2013 article-title: Ant‐based swarm algorithm for charging coordination of electric vehicles publication-title: Int J Dis Sens Netw – volume: 65 start-page: 1225 year: 2022 end-page: 1241 article-title: Object detection and localization using sparse‐FCM and optimization‐driven deep convolutional neural network publication-title: Comput J – volume: 67 start-page: 115 year: 2017 end-page: 122 article-title: A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system publication-title: Omega – volume: 3 start-page: 308 year: 2012 end-page: 315 article-title: Performance evaluation of an EDA‐based large‐scale plug‐in hybrid electric vehicle charging algorithm publication-title: IEEE Trans Smart Grid – volume: 71 start-page: 538 year: 2018 end-page: 552 article-title: Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm publication-title: Appl Soft Comput – volume: 20 start-page: 3386 issue: 9 year: 2018 end-page: 3396 article-title: Optimal charging scheduling by pricing for EV charging station with dual charging modes publication-title: IEEE Trans Intell Transp Syst – volume: 18 start-page: 1500 issue: 2 year: 2016 end-page: 1517 article-title: Smart charging for electric vehicles: a survey from the algorithmic perspective publication-title: IEEE Commun Surv Tutor – volume: 63 start-page: 900 issue: 6 year: 2020 end-page: 912 article-title: MapReduce and optimized deep network for rainfall prediction in agriculture publication-title: Comput J – volume: 6 start-page: 136 issue: 1 year: 2018 end-page: 148 article-title: Distributed routing and charging scheduling optimization for internet of electric vehicles publication-title: IEEE Internet Things J – volume: 4 start-page: 76 issue: 1 year: 2017 end-page: 88 article-title: Smart charging strategy for electric vehicle charging stations publication-title: IEEE Trans Transp Electrification – volume: 142 start-page: 351 year: 2017 end-page: 361 article-title: Metaheuristic optimization algorithms for the optimal coordination of plug‐in electric vehicle charging in distribution systems with distributed generation publication-title: Electr Pow Syst Res – volume: 11 start-page: 4949 issue: 6 year: 2020 end-page: 4959 article-title: Charge scheduling of electric vehicles in smart parking‐lot under future demands uncertainty publication-title: IEEE Trans Smart Grid – volume: 177 start-page: 354 year: 2016 end-page: 365 article-title: A multi‐agent based scheduling algorithm for adaptive electric vehicles charging publication-title: Appl Energy – volume: 21 start-page: 1 issue: 3 year: 2022 end-page: 18 article-title: How higher‐order personal values affect the purchase of electricity storage‐evidence from the German photovoltaic market publication-title: J Consum Behav – volume: 33 issue: 6 year: 2020 article-title: A modified rider optimization algorithm for multihop routing in WSN publication-title: Int J Numer Model Electron Netw Devices Fields – volume: 175 start-page: 113 year: 2019 end-page: 122 article-title: Joint routing and scheduling for electric vehicles in smart grids with V2G publication-title: Energy – volume: 14 start-page: 2894 issue: 7 year: 2017 end-page: 2902 article-title: Multiaggregator collaborative electric vehicle charge scheduling under variable energy purchase and EV cancelation events publication-title: IEEE Trans Industri Inform – volume: 143 start-page: 15 year: 2017 end-page: 20 article-title: A framework for electric vehicle (EV) charging in Singapore publication-title: Energy Procedia – volume: 10 start-page: 3020 issue: 3 year: 2018 end-page: 3030 article-title: Electric vehicle charge scheduling mechanism to maximize cost efficiency and user convenience publication-title: IEEE Trans Smart Grid – volume: 3 start-page: 1779 issue: 4 year: 2012 end-page: 1789 article-title: Decentralized plug‐in electric vehicle charging selection algorithm in power systems publication-title: IEEE Trans Smart Grid – volume: 73 start-page: 173 year: 2015 end-page: 181 article-title: Online optimal charging strategy for electric vehicles publication-title: Energy Procedia – volume: 4 start-page: 35 issue: 1 year: 2021 end-page: 41 article-title: Integrating renewable energy sources in electric vehicles via optimization assisted model publication-title: J Comput Mech Power Syst Control – volume: 26 start-page: 5113 year: 2020 end-page: 5132 article-title: Taylor kernel fuzzy C‐means clustering algorithm for trust and energy‐aware cluster head selection in wireless sensor networks publication-title: Wirel Netw – volume: 147 start-page: 31 year: 2017 end-page: 41 article-title: Commercial electric vehicle fleet scheduling for secondary frequency control publication-title: Electr Pow Syst Res – volume: 44 start-page: 473 year: 2015 end-page: 495 article-title: GHG footprint of major cities in India publication-title: Renew Sustain Energy Rev – volume: 56 start-page: 6914 issue: 6 year: 2020 end-page: 6924 article-title: Electric vehicle driver response evaluation in multiaggregator charging management with EV routing publication-title: IEEE Trans Ind Appl – year: 2014 article-title: A clustering approach for the‐diversity model in privacy preserving data mining using fractional calculus‐bacterial foraging optimization algorithm publication-title: Adv Comput Eng – ident: e_1_2_9_25_1 doi: 10.1016/j.epsr.2016.09.018 – ident: e_1_2_9_31_1 – ident: e_1_2_9_4_1 doi: 10.1109/TII.2017.2778762 – volume: 33 issue: 6 year: 2020 ident: e_1_2_9_18_1 article-title: A modified rider optimization algorithm for multihop routing in WSN publication-title: Int J Numer Model Electron Netw Devices Fields doi: 10.1002/jnm.2764 – ident: e_1_2_9_23_1 doi: 10.1016/j.omega.2016.04.005 – ident: e_1_2_9_22_1 doi: 10.1016/j.epsr.2017.02.019 – ident: e_1_2_9_8_1 doi: 10.1007/978-3-319-74461-2_3 – ident: e_1_2_9_14_1 doi: 10.1093/comjnl/bxz164 – ident: e_1_2_9_19_1 doi: 10.1007/s11276-020-02352-w – ident: e_1_2_9_30_1 doi: 10.1016/j.energy.2019.02.184 – ident: e_1_2_9_7_1 doi: 10.1109/TTE.2017.2753403 – ident: e_1_2_9_26_1 doi: 10.1016/j.asoc.2018.07.008 – ident: e_1_2_9_17_1 doi: 10.1093/comjnl/bxaa173 – volume: 9 year: 2013 ident: e_1_2_9_21_1 article-title: Ant‐based swarm algorithm for charging coordination of electric vehicles publication-title: Int J Dis Sens Netw – ident: e_1_2_9_29_1 doi: 10.1109/TIA.2020.3017563 – ident: e_1_2_9_16_1 doi: 10.1016/j.apenergy.2016.05.034 – ident: e_1_2_9_10_1 – ident: e_1_2_9_34_1 doi: 10.1155/2014/396529 – ident: e_1_2_9_13_1 doi: 10.1109/TSG.2012.2217761 – ident: e_1_2_9_15_1 doi: 10.46253/jcmps.v4i1.a5 – ident: e_1_2_9_11_1 doi: 10.1109/JIOT.2018.2876004 – ident: e_1_2_9_6_1 doi: 10.1016/j.egypro.2017.12.641 – ident: e_1_2_9_20_1 doi: 10.1016/j.egypro.2015.07.667 – ident: e_1_2_9_3_1 doi: 10.1016/j.rser.2014.12.036 – ident: e_1_2_9_24_1 doi: 10.1109/TSG.2011.2151888 – ident: e_1_2_9_5_1 doi: 10.1109/COMST.2016.2518628 – ident: e_1_2_9_27_1 doi: 10.1109/TIA.2020.2990096 – ident: e_1_2_9_28_1 doi: 10.1109/TSG.2020.3000850 – ident: e_1_2_9_32_1 doi: 10.1109/ICPADS.2011.42 – ident: e_1_2_9_36_1 doi: 10.1002/2050-7038.12593 – ident: e_1_2_9_9_1 doi: 10.1109/TITS.2018.2876287 – ident: e_1_2_9_33_1 doi: 10.1109/TSG.2018.2817067 – ident: e_1_2_9_2_1 doi: 10.1016/j.scs.2021.102820 – volume: 10 issue: 5 year: 2019 ident: e_1_2_9_35_1 article-title: Sea lion optimization algorithm publication-title: Int J Adv Comput Sci Appl – volume: 21 start-page: 1 issue: 3 year: 2022 ident: e_1_2_9_12_1 article-title: How higher‐order personal values affect the purchase of electricity storage‐evidence from the German photovoltaic market publication-title: J Consum Behav |
| SSID | ssj0011031 |
| Score | 2.3597116 |
| Snippet | Summary
In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for... In modern days, electric vehicles are quickly industrialized as well as their penetration is also increased highly, which brings more challenges for the power... |
| SourceID | proquest crossref wiley |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| SubjectTerms | Algorithms Charging charging scheduling Electric charge Electric vehicles Fitness Fractional calculus Optimization Route planning Scheduling sea lion optimization algorithm social optimization algorithm |
| Title | Hybrid optimization enabled multi‐aggregator‐based charge scheduling of electric vehicle in internet of electric vehicles |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcpe.7654 https://www.proquest.com/docview/2789158926 |
| Volume | 35 |
| WOSCitedRecordID | wos000937575600001&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: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1532-0634 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0011031 issn: 1532-0626 databaseCode: DRFUL dateStart: 20010101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1fS8MwED90-uCL_8XplAiiT3VtmqTNo8wNH0REFHwrbXKdA93GNgUfBD-Cn9FPYpK2m4KC4FMpTdqSu8vdJbnfD-DQ5MUhGkfqceSxSVBC5UmhI7fJGwcijQXLHNlEdHkZ393Jq_JUpa2FKfAhpgtu1jLcfG0NPM3GzRloqBriSSQ4m4cFatSW1WDh7LpzezHdQ7AEBgVaKvV8E7dX0LM-bVZ9vzujWYT5NU51jqaz8p9fXIXlMrwkp4U-rMEc9tdhpaJuIKUlb8Dr-Yst1SIDM2M8lqWYBF0dlSbukOHH23vaNcl412bl5sa6O00csBISkxIbF2Ur2ckgJwWVTk-RZ7y3nyW9Pum5lUac_PR8vAm3nfZN69wrmRg8ZcIB5mnl6zQNeZYjw9hYrYqRRUgzGuogRZ0xaZJy425llAmhOM-ZCTuEFKkO8wjzcAtq_UEft4FIJXOfIyqfKkYxizHKUdgXBjnXUtbhuBJJokqYcsuW8ZAUAMs0MaOa2FGtw8G05bCA5vihTaOSalIa5zixxb8BjyUVdThy8vu1f9K6atvrzl8b7sKSJaS3-02UN6A2GT3hHiyq50lvPNovVfQTY3DvwA |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1fS8MwED90Cvrif3H-jSD6VNelSdrgk6hj4hwiCr6VNrnqQDdxU_BB8CP4Gf0kJmk7FRQEn0pp0obcXe4u6f1-AFsmLw7QOFKPI49MghIoTwodukPeqC6SSLDUkU2E7XZ0dSXPRmCvrIXJ8SGGG27WMtx6bQ3cbkjXPlFD1T3uhoKzURhjRot4BcYOzxuXreEhgmUwyOFSqeebwL3EnvVprez73Rt9hphfA1XnaRrT_xrjDEwVASbZzzViFkawOwfTJXkDKWx5Hl6az7ZYi_TMmnFXFGMSdJVUmrjfDN9f35Jrk45f27zc3FiHp4mDVkJikmLjpGwtO-llJCfT6SjyhDf2s6TTJR2314iDn573F-CycXRx0PQKLgZPmYCAeVr5OkkCnmbIMDJ2qyJkIdKUBrqeoE6ZNGm5cbgyTIVQnGfMBB5CikQHWYhZsAiVbq-LS0CkkpnPEZVPFaOYRhhmKOwL6xnXUlZhp5RJrAqgcsuXcRvnEMs0NrMa21mtwuaw5X0OzvFDm9VSrHFhnv3Ylv_WeSSpqMK2E-Cv_eODsyN7Xf5rww2YaF6ctuLWcftkBSYtPb09faJ8FSqDh0dcg3H1NOj0H9YLff0AqpTzsA |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1fa9swED-6doy9rO22svSvCqN98mrLkmyxp9IkpDSEUBbIm7GlUxvoktBkhT4M-hH6GftJJsl22kIHhT4Z45MtJJ3uTuf7_QC-27g4RmtIA448tQFKrAIpdOKTvGkk8lSwwpNNJL1eOhzK_hL8rGthSnyIxYGb0wy_XzsFx6k2R4-ooWqKPxLB2TtYYVwKq5UrzfP2oLtIIjgGgxIulQahddxr7NmQHtVtn1ujRxfzqaPqLU179U19XINPlYNJjssVsQ5LOP4MqzV5A6l0-Qv87dy6Yi0ysXvG76oYk6CvpNLE_2b4cHefX9hw_MLF5fbGGTxNPLQSEhsUWyPlatnJxJCSTGekyA1eus-S0ZiM_Fkjzl96PvsKg3br10knqLgYAmUdAhZoFeo8j3lhkGFq9ValyBKkBY11lKMumLRhuTW4MimEUJwbZh0PIUWuY5OgiTdgeTwZ4zcgUkkTckQVUsUoFikmBoV7YWS4lrIBh_WcZKoCKnd8GVdZCbFMMzuqmRvVBuwvJKclOMcLMtv1tGaVes4yV_4b8VRS0YADP4H_bZ-d9FvuuvlawT340G-2s-5p72wLPjp2epd8onwblufXf3AH3qub-Wh2vVst139Kg_Mr |
| 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=Hybrid+optimization+enabled+multi%E2%80%90aggregator%E2%80%90based+charge+scheduling+of+electric+vehicle+in+internet+of+electric+vehicles&rft.jtitle=Concurrency+and+computation&rft.au=Suresh%2C+Pandian&rft.au=Shobana%2C+Selvaraj&rft.au=Ramya%2C+Ganesan&rft.au=Belsam+Jeba+Ananth%2C+Manasea+Selvin&rft.date=2023-04-25&rft.pub=John+Wiley+%26+Sons%2C+Inc&rft.issn=1532-0626&rft.eissn=1532-0634&rft.volume=35&rft.issue=9&rft.epage=n%2Fa&rft_id=info:doi/10.1002%2Fcpe.7654&rft.externalDBID=10.1002%252Fcpe.7654&rft.externalDocID=CPE7654 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1532-0626&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1532-0626&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1532-0626&client=summon |