A New Improved Model of Marine Predator Algorithm for Optimization Problems

The marine predator algorithm is a new nature-inspired metaheuristic algorithm that mimics biological interaction between marine predators and prey. It has been also stated from the literature that this algorithm can solve many real-world optimization problems which made it a new popular optimizatio...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Arabian journal for science and engineering (2011) Ročník 46; číslo 9; s. 8803 - 8826
Hlavní autoři:	Ramezani, Mehdi, Bahmanyar, Danial, Razmjooy, Navid
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021 Springer Nature B.V
Témata:	D C motors Electric motors Engineering Heuristic methods Humanities and Social Sciences Local optimization Machine learning Marine biology multidisciplinary Optimization algorithms Optimization techniques Particle swarm optimization Predator-prey simulation Predators Proportional integral derivative Research Article-Computer Engineering and Computer Science Science Search algorithms Simulation Marine predator algorithm CEC-06 2019 tests PID control DC motor Optimization
ISSN:	2193-567X, 1319-8025, 2191-4281
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	The marine predator algorithm is a new nature-inspired metaheuristic algorithm that mimics biological interaction between marine predators and prey. It has been also stated from the literature that this algorithm can solve many real-world optimization problems which made it a new popular optimization technique for the researchers. However, there is still a deficiency in the marine predator algorithm such as the inability to produce a diverse initial population with high productivity, lack of quick escaping of the local optimization, and lack of widely and broadly exploration of the search space. In the present study, a developed version of this algorithm is proposed based on the opposition-based learning method, chaos map, self-adaptive of population, and switching between exploration and exploitation phases. The simulations are performed using MATLAB environment on standard test functions including CEC-06 2019 tests and a real-world optimization problem based on PID control applied to a DC motor to evaluate the performance of the suggested algorithm. The simulation results are compared with the original marine predator algorithm and five state-of-the-art optimization algorithms namely Particle Swarm Optimization, Grasshopper Optimization Algorithm, JAYA Algorithm, Equilibrium optimizer Algorithm, Whale Optimization Algorithm, Differential Search Algorithm, and League Championship Algorithm. Eventually, the simulation results proved that the suggested algorithm has better results compared with other algorithms for the studied case studies.
AbstractList	The marine predator algorithm is a new nature-inspired metaheuristic algorithm that mimics biological interaction between marine predators and prey. It has been also stated from the literature that this algorithm can solve many real-world optimization problems which made it a new popular optimization technique for the researchers. However, there is still a deficiency in the marine predator algorithm such as the inability to produce a diverse initial population with high productivity, lack of quick escaping of the local optimization, and lack of widely and broadly exploration of the search space. In the present study, a developed version of this algorithm is proposed based on the opposition-based learning method, chaos map, self-adaptive of population, and switching between exploration and exploitation phases. The simulations are performed using MATLAB environment on standard test functions including CEC-06 2019 tests and a real-world optimization problem based on PID control applied to a DC motor to evaluate the performance of the suggested algorithm. The simulation results are compared with the original marine predator algorithm and five state-of-the-art optimization algorithms namely Particle Swarm Optimization, Grasshopper Optimization Algorithm, JAYA Algorithm, Equilibrium optimizer Algorithm, Whale Optimization Algorithm, Differential Search Algorithm, and League Championship Algorithm. Eventually, the simulation results proved that the suggested algorithm has better results compared with other algorithms for the studied case studies.
Author	Bahmanyar, Danial Razmjooy, Navid Ramezani, Mehdi
Author_xml	– sequence: 1 givenname: Mehdi surname: Ramezani fullname: Ramezani, Mehdi organization: Department of Electrical and Control Engineering, Tafresh University – sequence: 2 givenname: Danial surname: Bahmanyar fullname: Bahmanyar, Danial organization: Department of Electrical and Control Engineering, Tafresh University – sequence: 3 givenname: Navid orcidid: 0000-0002-0102-1482 surname: Razmjooy fullname: Razmjooy, Navid email: navid.razmjooy@hotmail.com organization: Independent Researcher
BookMark	eNp9kE1LAzEQhoNUsNb-AU8Bz6v52E2TYyl-FFvrQcFbyGaTGtnd1GSr6K837QqCh55mBt5n5p33FAxa3xoAzjG6xAhNriKmlIkMEZyhgnGe0SMwJFjgLCccD_Y9zQo2eTkB4xhdiXJORYExHYL7KXwwn3DebIL_MBVc-srU0Fu4VMG1Bj4GU6nOBzit1z647rWBNk2rTeca960659uk8WVtmngGjq2qoxn_1hF4vrl-mt1li9XtfDZdZJpi0WWVzU2uSKUtQsXEsmTHClUKXFqOVa51jqwoBSPUMjGxVAvBtS45EhYrUQk6Ahf93uT5fWtiJ9_8NrTppCQFYzlBpKBJRXqVDj7GYKzcBNeo8CUxkrvcZJ-bTLnJfW5yB_F_kHbd_ssuKFcfRmmPxnSnXZvw5-oA9QMWH4QW
CitedBy_id	crossref_primary_10_1016_j_engappai_2023_106207 crossref_primary_10_3390_s22155779 crossref_primary_10_1002_cpe_6975 crossref_primary_10_1007_s11227_022_04903_8 crossref_primary_10_1155_2022_7311245 crossref_primary_10_1080_0305215X_2025_2464862 crossref_primary_10_1002_ima_22852 crossref_primary_10_1007_s40313_022_00909_y crossref_primary_10_1016_j_engappai_2022_105715 crossref_primary_10_1155_2022_1631914 crossref_primary_10_1007_s11831_023_09912_1 crossref_primary_10_1155_2021_9651957 crossref_primary_10_3103_S1060992X25700134 crossref_primary_10_1155_2021_5122962 crossref_primary_10_3390_pr11102989 crossref_primary_10_1155_2022_5202265 crossref_primary_10_3390_math10091411 crossref_primary_10_1002_ird_2912 crossref_primary_10_1088_2631_8695_adb23f crossref_primary_10_1007_s13369_023_08217_6 crossref_primary_10_1007_s11831_023_09897_x crossref_primary_10_1007_s12206_024_0929_8 crossref_primary_10_1007_s42835_024_01865_0 crossref_primary_10_3390_fi14100281 crossref_primary_10_1002_cpe_7612 crossref_primary_10_1007_s12530_023_09557_2 crossref_primary_10_1016_j_chaos_2023_113421 crossref_primary_10_1007_s42835_023_01560_6 crossref_primary_10_1109_JSEN_2023_3287582 crossref_primary_10_3390_math10071100 crossref_primary_10_1007_s42835_023_01717_3 crossref_primary_10_1016_j_bspc_2023_105870 crossref_primary_10_1002_ima_22888 crossref_primary_10_1038_s41598_025_98033_9 crossref_primary_10_1016_j_egyr_2021_10_090 crossref_primary_10_1007_s12083_024_01756_1 crossref_primary_10_1007_s12065_023_00838_y crossref_primary_10_1093_jcde_qwae004 crossref_primary_10_1080_15567036_2023_2276385 crossref_primary_10_1002_cta_3152 crossref_primary_10_1016_j_egyr_2023_04_015 crossref_primary_10_3390_diagnostics13142454 crossref_primary_10_3390_su15010400 crossref_primary_10_1049_rpg2_12744 crossref_primary_10_1016_j_eswa_2025_126864 crossref_primary_10_3390_math11224621 crossref_primary_10_3390_fi14100297 crossref_primary_10_1038_s41598_024_71122_x crossref_primary_10_1038_s41598_025_91466_2 crossref_primary_10_1007_s42835_023_01556_2 crossref_primary_10_1109_TGRS_2024_3422475 crossref_primary_10_3390_drones9040252 crossref_primary_10_1038_s41598_025_93365_y crossref_primary_10_1007_s13369_022_06636_5 crossref_primary_10_1016_j_ijepes_2024_110266 crossref_primary_10_1016_j_knosys_2024_111775 crossref_primary_10_1109_ACCESS_2023_3319596 crossref_primary_10_1016_j_matcom_2024_01_012 crossref_primary_10_3390_s22145425 crossref_primary_10_1016_j_seta_2023_103364 crossref_primary_10_1007_s12596_025_02464_6 crossref_primary_10_1080_15325008_2023_2228795 crossref_primary_10_1088_1402_4896_ad86f7 crossref_primary_10_1093_jcde_qwae060 crossref_primary_10_1016_j_seta_2022_102176 crossref_primary_10_3390_rs17081325 crossref_primary_10_1007_s41939_024_00490_8 crossref_primary_10_1016_j_ijhydene_2022_07_251 crossref_primary_10_1080_15567036_2024_2327597 crossref_primary_10_3390_jmse11061163 crossref_primary_10_3390_axioms13010033 crossref_primary_10_1016_j_egyr_2021_08_134 crossref_primary_10_1007_s42044_025_00317_w crossref_primary_10_1038_s41598_025_85273_y crossref_primary_10_1007_s42235_024_00548_w crossref_primary_10_1016_j_energy_2022_124516 crossref_primary_10_1007_s10462_021_10086_0
Cites_doi	10.1016/j.engappai.2013.12.004 10.1007/978-3-030-16339-6_5 10.18517/ijaseit.1.4.93 10.1016/j.cie.2019.106040 10.1007/s00521-019-04132-w 10.1016/j.aeue.2018.05.022 10.1007/978-3-030-39415-8 10.1016/j.jclepro.2019.119414 10.1016/j.advengsoft.2016.01.008 10.1016/j.ijrefrig.2017.06.024 10.1080/08839514.2020.1712789 10.1016/j.knosys.2019.105190 10.1109/ACCESS.2020.2974498 10.1016/j.knosys.2019.105277 10.1016/j.eswa.2020.113377 10.1016/j.engappai.2018.03.003 10.1016/j.eswa.2020.113340 10.1016/j.cnsns.2012.06.009 10.1016/j.egyr.2020.04.012 10.1016/j.asoc.2013.12.005 10.1016/S0045-7825(01)00323-1 10.1016/j.advengsoft.2017.01.004 10.1007/s00542-018-3920-4 10.1016/j.cageo.2011.12.011 10.1201/9780429123641 10.1002/ima.22495 10.1007/s11081-019-09438-1 10.1016/j.asoc.2020.107054 10.1109/CIMCA.2005.1631345
ContentType	Journal Article
Copyright	King Fahd University of Petroleum & Minerals 2021 King Fahd University of Petroleum & Minerals 2021.
Copyright_xml	– notice: King Fahd University of Petroleum & Minerals 2021 – notice: King Fahd University of Petroleum & Minerals 2021.
DBID	AAYXX CITATION
DOI	10.1007/s13369-021-05688-3
DatabaseName	CrossRef
DatabaseTitle	CrossRef
DatabaseTitleList
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2191-4281
EndPage	8826
ExternalDocumentID	10_1007_s13369_021_05688_3
GroupedDBID	-EM 0R~ 203 2KG 406 AAAVM AACDK AAHNG AAIAL AAJBT AANZL AARHV AASML AATNV AATVU AAUYE AAYTO AAYZH ABAKF ABDBF ABDZT ABECU ABFTD ABFTV ABJNI ABJOX ABKCH ABMQK ABQBU ABSXP ABTEG ABTKH ABTMW ABXPI ACAOD ACBXY ACDTI ACHSB ACMDZ ACMLO ACOKC ACPIV ACUHS ACZOJ ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFQL AEJRE AEMSY AEOHA AESKC AEVLU AEXYK AFBBN AFLOW AFQWF AGAYW AGJBK AGMZJ AGQEE AGQMX AGRTI AHAVH AHBYD AHSBF AIAKS AIGIU AILAN AITGF AJBLW AJRNO AJZVZ ALFXC ALMA_UNASSIGNED_HOLDINGS AMXSW AMYLF AOCGG AXYYD BGNMA CSCUP DDRTE DNIVK DPUIP EBLON EBS EIOEI EJD ESX FERAY FIGPU FINBP FNLPD FSGXE GGCAI GQ6 GQ7 H13 HG6 I-F IKXTQ IWAJR J-C JBSCW JZLTJ L8X LLZTM M4Y MK~ NPVJJ NQJWS NU0 O9J PT4 ROL RSV SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE TSG TUS UOJIU UTJUX UZXMN VFIZW Z5O Z7R Z7V Z7X Z7Y Z7Z Z81 Z83 Z85 Z88 ZMTXR ~8M AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC AEZWR AFDZB AFHIU AFOHR AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION 06D 0VY 23M 29~ 2KM 30V 408 5GY 96X AAJKR AARTL AAYIU AAYQN AAZMS ABTHY ACGFS ACKNC ADHHG ADHIR AEGNC AEJHL AENEX AEPYU AETCA AFWTZ AFZKB AGDGC AGWZB AGYKE AHYZX AIIXL AMKLP AMYQR ANMIH AYJHY ESBYG FFXSO FRRFC FYJPI GGRSB GJIRD GX1 HMJXF HRMNR HZ~ I0C IXD J9A KOV O93 OVT P9P R9I RLLFE S27 S3B SEG SHX T13 U2A UG4 VC2 W48 WK8 ~A9
ID	FETCH-LOGICAL-c319t-df4e4a2dcf0057f6b04f9ab91bf81a4cc40f9b9623f697f3c998ccb809f1a9d93
IEDL.DBID	RSV
ISICitedReferencesCount	102
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000646519700002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2193-567X 1319-8025
IngestDate	Mon Jun 30 09:05:57 EDT 2025 Sat Nov 29 02:51:38 EST 2025 Tue Nov 18 22:40:02 EST 2025 Fri Feb 21 02:48:40 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	9
Keywords	Marine predator algorithm CEC-06 2019 tests PID control DC motor Optimization
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c319t-df4e4a2dcf0057f6b04f9ab91bf81a4cc40f9b9623f697f3c998ccb809f1a9d93
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-0102-1482
PQID	2566420253
PQPubID	2044268
PageCount	24
ParticipantIDs	proquest_journals_2566420253 crossref_primary_10_1007_s13369_021_05688_3 crossref_citationtrail_10_1007_s13369_021_05688_3 springer_journals_10_1007_s13369_021_05688_3
PublicationCentury	2000
PublicationDate	2021-09-01
PublicationDateYYYYMMDD	2021-09-01
PublicationDate_xml	– month: 09 year: 2021 text: 2021-09-01 day: 01
PublicationDecade	2020
PublicationPlace	Berlin/Heidelberg
PublicationPlace_xml	– name: Berlin/Heidelberg – name: Heidelberg
PublicationTitle	Arabian journal for science and engineering (2011)
PublicationTitleAbbrev	Arab J Sci Eng
PublicationYear	2021
Publisher	Springer Berlin Heidelberg Springer Nature B.V
Publisher_xml	– name: Springer Berlin Heidelberg – name: Springer Nature B.V
References	Coello (CR2) 2002; 191 Solihin, Tack, Kean (CR36) 2011; 1 Vanderbei (CR4) 2020 Saremi, Mirjalili, Lewis (CR29) 2017; 105 Cuevas, Fausto, González (CR1) 2020 CR39 Rodrigues, de Rosa, Passos, Papa (CR13) 2020 Faramarzi, Heidarinejad, Stephens, Mirjalili (CR30) 2020; 191 CR15 Rao, Pawar (CR14) 2020; 34 CR35 CR34 CR10 Namadchian, Ramezani, Razmjooy (CR7) 2016; 10 Liang, Kou, Wen (CR16) 2020; 8 Faramarzi, Heidarinejad, Mirjalili, Gandomi (CR19) 2020; 152 Bansal (CR27) 2019 Gandomi, Yang, Talatahari, Alavi (CR22) 2013; 18 Guo, Dai, Jermsittiparsert, Razmjooy (CR25) 2020; 6 Rao (CR28) 2016; 7 Pelusi, Mascella, Tallini, Nayak, Naik, Deng (CR17) 2020; 191 Mortazavi, Toğan, Nuhoğlu (CR8) 2018; 71 CR3 CR6 Ezugwu, Adeleke, Akinyelu, Viriri (CR12) 2020; 32 Kashan (CR33) 2014; 16 Zahir, Alhady, Othman, Ahmad (CR38) 2018 Wu, Wang, Burrage, Tian, Lawson, Ding (CR18) 2020; 149 Mirjalili, Lewis (CR31) 2016; 95 CR9 Luus (CR5) 2019 Civicioglu (CR32) 2012; 46 CR20 Ravipudi, Neebha (CR23) 2018; 92 Tian, Yan, Han, Nojavan, Jermsittiparsert, Razmjooy (CR24) 2020; 249 Xu, Wang, Wang, Hei, Zhao (CR21) 2014; 29 Rao, More (CR26) 2017; 82 Agarwal, Parmar, Gupta, Sikander (CR37) 2018; 24 Dokeroglu, Sevinc, Kucukyilmaz, Cosar (CR11) 2019; 137 RV Rao (5688_CR14) 2020; 34 5688_CR15 A Faramarzi (5688_CR19) 2020; 152 AH Kashan (5688_CR33) 2014; 16 5688_CR39 M-W Tian (5688_CR24) 2020; 249 R Rao (5688_CR28) 2016; 7 MI Solihin (5688_CR36) 2011; 1 AE Ezugwu (5688_CR12) 2020; 32 J Wu (5688_CR18) 2020; 149 JL Ravipudi (5688_CR23) 2018; 92 AH Gandomi (5688_CR22) 2013; 18 RJ Vanderbei (5688_CR4) 2020 D Rodrigues (5688_CR13) 2020 A Zahir (5688_CR38) 2018 R Rao (5688_CR26) 2017; 82 JC Bansal (5688_CR27) 2019 Y Guo (5688_CR25) 2020; 6 5688_CR10 5688_CR35 S Saremi (5688_CR29) 2017; 105 P Civicioglu (5688_CR32) 2012; 46 5688_CR34 T Dokeroglu (5688_CR11) 2019; 137 Q Xu (5688_CR21) 2014; 29 X Liang (5688_CR16) 2020; 8 A Faramarzi (5688_CR30) 2020; 191 S Mirjalili (5688_CR31) 2016; 95 E Cuevas (5688_CR1) 2020 5688_CR9 D Pelusi (5688_CR17) 2020; 191 5688_CR6 J Agarwal (5688_CR37) 2018; 24 CAC Coello (5688_CR2) 2002; 191 R Luus (5688_CR5) 2019 5688_CR3 5688_CR20 A Namadchian (5688_CR7) 2016; 10 A Mortazavi (5688_CR8) 2018; 71
References_xml	– volume: 10 start-page: 49 issue: 4 year: 2016 ident: CR7 article-title: A new meta-heuristic algorithm for optimization based on variance reduction of guassian distribution publication-title: Majlesi J. Electrical Eng. – volume: 29 start-page: 1 year: 2014 end-page: 12 ident: CR21 article-title: A review of opposition-based learning from 2005 to 2012 publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2013.12.004 – start-page: 139 year: 2020 end-page: 159 ident: CR1 article-title: The Locust Swarm Optimization Algorithm publication-title: New Advancements in Swarm Algorithms: Operators and Applications doi: 10.1007/978-3-030-16339-6_5 – volume: 1 start-page: 458 year: 2011 end-page: 461 ident: CR36 article-title: Tuning of PID controller using particle swarm optimization (PSO) publication-title: Proceed. Int. Conf. Adv. Sci., Eng. Inf. Technol. doi: 10.18517/ijaseit.1.4.93 – start-page: 427 year: 2018 end-page: 437 ident: CR38 article-title: Genetic Algorithm Optimization of PID Controller for Brushed DC Motor publication-title: Intelligent Manufacturing & Mechatronics – volume: 137 start-page: 106040 year: 2019 ident: CR11 article-title: A survey on new generation metaheuristic algorithms publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2019.106040 – volume: 32 start-page: 6207 issue: 10 year: 2020 end-page: 6251 ident: CR12 article-title: A conceptual comparison of several metaheuristic algorithms on continuous optimisation problems publication-title: Neural Comput. Appl. doi: 10.1007/s00521-019-04132-w – volume: 92 start-page: 54 year: 2018 end-page: 63 ident: CR23 article-title: Synthesis of linear antenna arrays using jaya, self-adaptive jaya and chaotic jaya algorithms publication-title: AEU-International Journal of Electronics and Communications doi: 10.1016/j.aeue.2018.05.022 – year: 2020 ident: CR4 publication-title: Linear programming: foundations and extensions doi: 10.1007/978-3-030-39415-8 – volume: 249 start-page: 119414 year: 2020 ident: CR24 article-title: New optimal design for a hybrid solar chimney, solid oxide electrolysis and fuel cell based on improved deer hunting optimization algorithm publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2019.119414 – start-page: 11 year: 2019 end-page: 23 ident: CR27 article-title: Particle swarm optimization publication-title: Evolutionary and swarm intelligence algorithms – ident: CR39 – volume: 95 start-page: 51 year: 2016 end-page: 67 ident: CR31 article-title: The whale optimization algorithm publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2016.01.008 – volume: 82 start-page: 312 year: 2017 end-page: 324 ident: CR26 article-title: Optimal design and analysis of mechanical draft cooling tower using improved Jaya algorithm publication-title: Int. J. Refrig doi: 10.1016/j.ijrefrig.2017.06.024 – ident: CR10 – ident: CR35 – ident: CR6 – volume: 34 start-page: 187 issue: 3 year: 2020 end-page: 250 ident: CR14 article-title: Self-adaptive multi-population Rao algorithms for engineering design optimization publication-title: Appl. Artif. Intell. doi: 10.1080/08839514.2020.1712789 – volume: 191 start-page: 105190 year: 2020 ident: CR30 article-title: Equilibrium optimizer: A novel optimization algorithm publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2019.105190 – volume: 8 start-page: 49543 year: 2020 end-page: 49550 ident: CR16 article-title: An Improved Chicken Swarm Optimization Algorithm and its Application in Robot Path Planning publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2974498 – ident: CR3 – ident: CR15 – volume: 191 start-page: 105277 year: 2020 ident: CR17 article-title: An Improved Moth-Flame Optimization algorithm with hybrid search phase publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2019.105277 – volume: 152 start-page: 113377 year: 2020 ident: CR19 article-title: Marine predators algorithm: A nature-inspired Metaheuristic publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113377 – volume: 71 start-page: 275 year: 2018 end-page: 292 ident: CR8 article-title: Interactive search algorithm: a new hybrid metaheuristic optimization algorithm publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2018.03.003 – start-page: 1 year: 2020 end-page: 21 ident: CR13 article-title: Adaptive improved flower pollination algorithm for global optimization publication-title: Nature-Inspired Computation in Data Mining and Machine Learning – volume: 149 start-page: 113340 year: 2020 ident: CR18 article-title: An improved firefly algorithm for global continuous optimization problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113340 – ident: CR9 – volume: 18 start-page: 89 issue: 1 year: 2013 end-page: 98 ident: CR22 article-title: Firefly algorithm with chaos publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2012.06.009 – volume: 6 start-page: 885 year: 2020 end-page: 894 ident: CR25 article-title: An optimal configuration for a battery and PEM fuel cell-based hybrid energy system using developed Krill herd optimization algorithm for locomotive application publication-title: Energy Rep. doi: 10.1016/j.egyr.2020.04.012 – ident: CR34 – volume: 16 start-page: 171 year: 2014 end-page: 200 ident: CR33 article-title: League Championship Algorithm (LCA): An algorithm for global optimization inspired by sport championships publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2013.12.005 – volume: 7 start-page: 19 issue: 1 year: 2016 end-page: 34 ident: CR28 article-title: Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems publication-title: Int. J. Ind. Eng. Comput. – volume: 191 start-page: 1245 issue: 11–12 year: 2002 end-page: 1287 ident: CR2 article-title: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/S0045-7825(01)00323-1 – volume: 105 start-page: 30 year: 2017 end-page: 47 ident: CR29 article-title: Grasshopper optimisation algorithm: theory and application publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2017.01.004 – volume: 24 start-page: 4997 issue: 12 year: 2018 end-page: 5006 ident: CR37 article-title: Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor publication-title: Microsyst. Technol. doi: 10.1007/s00542-018-3920-4 – ident: CR20 – volume: 46 start-page: 229 year: 2012 end-page: 247 ident: CR32 article-title: Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2011.12.011 – year: 2019 ident: CR5 publication-title: Iterative dynamic programming doi: 10.1201/9780429123641 – volume: 34 start-page: 187 issue: 3 year: 2020 ident: 5688_CR14 publication-title: Appl. Artif. Intell. doi: 10.1080/08839514.2020.1712789 – volume: 18 start-page: 89 issue: 1 year: 2013 ident: 5688_CR22 publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2012.06.009 – start-page: 11 volume-title: Evolutionary and swarm intelligence algorithms year: 2019 ident: 5688_CR27 – volume: 95 start-page: 51 year: 2016 ident: 5688_CR31 publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2016.01.008 – volume: 24 start-page: 4997 issue: 12 year: 2018 ident: 5688_CR37 publication-title: Microsyst. Technol. doi: 10.1007/s00542-018-3920-4 – volume: 6 start-page: 885 year: 2020 ident: 5688_CR25 publication-title: Energy Rep. doi: 10.1016/j.egyr.2020.04.012 – volume-title: Iterative dynamic programming year: 2019 ident: 5688_CR5 doi: 10.1201/9780429123641 – volume: 105 start-page: 30 year: 2017 ident: 5688_CR29 publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2017.01.004 – volume: 191 start-page: 105190 year: 2020 ident: 5688_CR30 publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2019.105190 – ident: 5688_CR9 doi: 10.1002/ima.22495 – volume: 149 start-page: 113340 year: 2020 ident: 5688_CR18 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113340 – ident: 5688_CR10 – ident: 5688_CR6 doi: 10.1007/s11081-019-09438-1 – volume: 1 start-page: 458 year: 2011 ident: 5688_CR36 publication-title: Proceed. Int. Conf. Adv. Sci., Eng. Inf. Technol. doi: 10.18517/ijaseit.1.4.93 – ident: 5688_CR15 doi: 10.1016/j.asoc.2020.107054 – ident: 5688_CR39 – volume: 191 start-page: 1245 issue: 11–12 year: 2002 ident: 5688_CR2 publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/S0045-7825(01)00323-1 – volume-title: Linear programming: foundations and extensions year: 2020 ident: 5688_CR4 doi: 10.1007/978-3-030-39415-8 – ident: 5688_CR3 – volume: 92 start-page: 54 year: 2018 ident: 5688_CR23 publication-title: AEU-International Journal of Electronics and Communications doi: 10.1016/j.aeue.2018.05.022 – start-page: 427 volume-title: Intelligent Manufacturing & Mechatronics year: 2018 ident: 5688_CR38 – ident: 5688_CR35 – volume: 191 start-page: 105277 year: 2020 ident: 5688_CR17 publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2019.105277 – volume: 152 start-page: 113377 year: 2020 ident: 5688_CR19 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113377 – ident: 5688_CR20 doi: 10.1109/CIMCA.2005.1631345 – volume: 7 start-page: 19 issue: 1 year: 2016 ident: 5688_CR28 publication-title: Int. J. Ind. Eng. Comput. – volume: 32 start-page: 6207 issue: 10 year: 2020 ident: 5688_CR12 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-019-04132-w – volume: 10 start-page: 49 issue: 4 year: 2016 ident: 5688_CR7 publication-title: Majlesi J. Electrical Eng. – volume: 71 start-page: 275 year: 2018 ident: 5688_CR8 publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2018.03.003 – volume: 137 start-page: 106040 year: 2019 ident: 5688_CR11 publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2019.106040 – volume: 46 start-page: 229 year: 2012 ident: 5688_CR32 publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2011.12.011 – volume: 249 start-page: 119414 year: 2020 ident: 5688_CR24 publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2019.119414 – volume: 82 start-page: 312 year: 2017 ident: 5688_CR26 publication-title: Int. J. Refrig doi: 10.1016/j.ijrefrig.2017.06.024 – start-page: 1 volume-title: Nature-Inspired Computation in Data Mining and Machine Learning year: 2020 ident: 5688_CR13 – volume: 8 start-page: 49543 year: 2020 ident: 5688_CR16 publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2974498 – volume: 16 start-page: 171 year: 2014 ident: 5688_CR33 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2013.12.005 – start-page: 139 volume-title: New Advancements in Swarm Algorithms: Operators and Applications year: 2020 ident: 5688_CR1 doi: 10.1007/978-3-030-16339-6_5 – volume: 29 start-page: 1 year: 2014 ident: 5688_CR21 publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2013.12.004 – ident: 5688_CR34
SSID	ssib048395113 ssj0001916267 ssj0061873
Score	2.5318239
Snippet	The marine predator algorithm is a new nature-inspired metaheuristic algorithm that mimics biological interaction between marine predators and prey. It has...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	8803
SubjectTerms	D C motors Electric motors Engineering Heuristic methods Humanities and Social Sciences Local optimization Machine learning Marine biology multidisciplinary Optimization algorithms Optimization techniques Particle swarm optimization Predator-prey simulation Predators Proportional integral derivative Research Article-Computer Engineering and Computer Science Science Search algorithms Simulation
Title	A New Improved Model of Marine Predator Algorithm for Optimization Problems
URI	https://link.springer.com/article/10.1007/s13369-021-05688-3 https://www.proquest.com/docview/2566420253
Volume	46
WOSCitedRecordID	wos000646519700002&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: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 2191-4281 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001916267 issn: 2193-567X databaseCode: RSV dateStart: 20110101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDI5gcIADb8RgoBy4QaS2ydrkOCEmJMSYeGm3Kk1rmLQHage_HydrKSBAgrPdqLLj-HPiByHHMkl1CMqwINIeE-AbpgPZZu0ERIYARSLVDZuIej05GKh-WRRWVNnu1ZOkO6nrYjfOQ8VsSgE6bdQvXyRL6O6kNceb24dqFwl0-YgieH3TgggocKNk0To5a4fRoKye-X7Zzx6qhp1fXkqdA-qu_-_XN8haCThpZ75DNslCNtkiqx_aEG6Tyw7Fs47O7xeylNr5aCM6BXqlbW0g7edZamNz2hk9TvPh7GlMEerSazxtxmUZJ_K4wTTFDrnvnt-dXbByyAIzaH0zlqJOhA5SA7YuFUIUICidKD8B6WthjPBAJQpREoQqAm4wPjMmkZ4CX6tU8V3SmEwn2R6hCDUCACUEYKgbSpBaZ0mkPFQ-aC9STeJXgo1N2YHcDsIYxXXvZCuoGAUVO0HFvElO3r95nvff-JW7VekrLm2xiBHUYZCF2A7Jp5V-avLPq-3_jf2ArAROxTYBrUUas_wlOyTL5nU2LPIjt0ffAJ-c3X0
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDI5gIAEH3ojBgBy4QaS2ydrmOCEm0B5MMNBuVZrWMGkP1A5-P07XUkCABGe7UWU78efED0JO_TBSLkjNHE9ZTICtmXL8OquHIGIEKD5Ss2ETXrfrDwaylxeFpUW2e_EkmZ3UZbEb565kJqUAnTbqly-SJYEeyyTy3d49FFYk0OUjiuDlTQsiICcbJYu7k7O66w3y6pnvl_3soUrY-eWlNHNAzY3__fomWc8BJ23MLWSLLMSTbbL2oQ3hDmk1KJ51dH6_EEfUzEcb0SnQjjK1gbSXxJGJzWlj9DhNhrOnMUWoS2_wtBnnZZzIkw2mSXfJffOyf3HF8iELTOPum7EIdSKUE2kwdangogBBqlDaIfi2EloLC2QoESWBKz3gGuMzrUPfkmArGUm-RyqT6STeJxShhgMghQAMdV0ffKXi0JMWKh-U5ckqsQvBBjrvQG4GYYyCsneyEVSAggoyQQW8Ss7ev3me99_4lbtW6CvI92IaIKjDIAuxHZLPC_2U5J9XO_gb-wlZuep32kH7uts6JKtOpm6TjFYjlVnyEh-RZf06G6bJcWavbwoG4GE
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT8MwDI5gIAQH3ojxzIEbROsja5vjBEygwZjEQ7tVaVrDpK2busLvx-mDDgRIiHPSSLWd-HNi-yPkxAtC6YBQzHKlwTiYiknLa7JmADxCgOLhaEY24Xa7Xr8vejNV_Fm2e_kkmdc06C5NcdqYhNCoCt9s2xFMpxegA0dd2_NkgWvSIB2v3z-VFsXR_SOisKtbF0RDVkYrizvVZk3H7ReVNN8v-9lbVRD0y6tp5ozaa___jXWyWgBR2sotZ4PMRfEmWZlpT7hFOi2KZyDN7x2ikGretCEdA72VumaQ9pIo1DE7bQ2fx8kgfRlRhMD0Dk-hUVHeiXMywprpNnlsXz6cX7GCfIEp3JUpC1FXXFqhAl2vCg4KE4QMhBmAZ0quFDdABALREzjCBVth3KZU4BkCTClCYe-QWjyOo11CEYJYAIJzwBDY8cCTMgpcYaBRgDRcUSdmKWRfFZ3JNUHG0K96KmtB-SgoPxOUb9fJ6cc3k7wvx6-zD0rd-cUenfoI9jD4QsyHw2elrqrhn1fb-9v0Y7LUu2j7N9fdzj5ZtjJt6xy1A1JLk9fokCyqt3QwTY4y030HrdrpRQ
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=A+New+Improved+Model+of+Marine+Predator+Algorithm+for+Optimization+Problems&rft.jtitle=Arabian+journal+for+science+and+engineering+%282011%29&rft.au=Ramezani%2C+Mehdi&rft.au=Bahmanyar%2C+Danial&rft.au=Razmjooy%2C+Navid&rft.date=2021-09-01&rft.issn=2193-567X&rft.eissn=2191-4281&rft.volume=46&rft.issue=9&rft.spage=8803&rft.epage=8826&rft_id=info:doi/10.1007%2Fs13369-021-05688-3&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s13369_021_05688_3
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2193-567X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2193-567X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2193-567X&client=summon