Continuous optimization algorithms for tuning real and integer parameters of swarm intelligence algorithms
The performance of optimization algorithms, including those based on swarm intelligence, depends on the values assigned to their parameters. To obtain high performance, these parameters must be fine-tuned. Since many parameters can take real values or integer values from a large domain, it is often...
Gespeichert in:
| Veröffentlicht in: | Swarm intelligence Jg. 6; H. 1; S. 49 - 75 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Boston
Springer US
01.03.2012
|
| Schlagworte: | |
| ISSN: | 1935-3812, 1935-3820 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | The performance of optimization algorithms, including those based on swarm intelligence, depends on the values assigned to their parameters. To obtain high performance, these parameters must be fine-tuned. Since many parameters can take real values or integer values from a large domain, it is often possible to treat the tuning problem as a continuous optimization problem. In this article, we study the performance of a number of prominent continuous optimization algorithms for parameter tuning using various case studies from the swarm intelligence literature. The continuous optimization algorithms that we study are enhanced to handle the stochastic nature of the tuning problem. In particular, we introduce a new post-selection mechanism that uses F-Race in the final phase of the tuning process to select the best among elite parameter configurations. We also examine the parameter space of the swarm intelligence algorithms that we consider in our study, and we show that by fine-tuning their parameters one can obtain substantial improvements over default configurations. |
|---|---|
| AbstractList | The performance of optimization algorithms, including those based on swarm intelligence, depends on the values assigned to their parameters. To obtain high performance, these parameters must be fine-tuned. Since many parameters can take real values or integer values from a large domain, it is often possible to treat the tuning problem as a continuous optimization problem. In this article, we study the performance of a number of prominent continuous optimization algorithms for parameter tuning using various case studies from the swarm intelligence literature. The continuous optimization algorithms that we study are enhanced to handle the stochastic nature of the tuning problem. In particular, we introduce a new post-selection mechanism that uses F-Race in the final phase of the tuning process to select the best among elite parameter configurations. We also examine the parameter space of the swarm intelligence algorithms that we consider in our study, and we show that by fine-tuning their parameters one can obtain substantial improvements over default configurations. |
| Author | Montes de Oca, Marco A. Birattari, Mauro Stützle, Thomas Yuan, Zhi |
| Author_xml | – sequence: 1 givenname: Zhi surname: Yuan fullname: Yuan, Zhi email: zyuan@ulb.ac.be organization: IRIDIA, CoDE, Université Libre de Bruxelles – sequence: 2 givenname: Marco A. surname: Montes de Oca fullname: Montes de Oca, Marco A. organization: IRIDIA, CoDE, Université Libre de Bruxelles, Dept. of Mathematical Sciences, University of Delaware – sequence: 3 givenname: Mauro surname: Birattari fullname: Birattari, Mauro organization: IRIDIA, CoDE, Université Libre de Bruxelles – sequence: 4 givenname: Thomas surname: Stützle fullname: Stützle, Thomas organization: IRIDIA, CoDE, Université Libre de Bruxelles |
| BookMark | eNp9kE1LAzEQhoNUsK3-AG_5A6v52DTJUYpfUPCi55DsZteU3aQkWUR_vWkrIh56GGZgeN5hngWY-eAtANcY3WCE-G3CmBNcIVwKrVglz8AcS8oqKgia_c6YXIBFSluEmKSUzsF2HXx2fgpTgmGX3ei-dHbBQz30Ibr8PibYhQjz5J3vYbR6gNq30PlsexvhTkc92mxjwTuYPnQcD7thcL31jf2TcwnOOz0ke_XTl-Dt4f51_VRtXh6f13ebqiFC5IoaziRi2CLT1DUVvKXCMFtr0q60MKIThmiKBG54TWreSi6k0cbUnDVs1WG6BPiY28SQUrSd2kU36vipMFJ7WeooSxVZai9LycLwf0zj8kFEjtoNJ0lyJFO54osStQ1T9OXBE9A3c62C3g |
| CitedBy_id | crossref_primary_10_1145_3680282 crossref_primary_10_1155_2021_6636150 crossref_primary_10_3390_a9010003 crossref_primary_10_1002_net_22185 crossref_primary_10_1007_s00521_025_11423_y crossref_primary_10_1016_j_asoc_2015_03_051 crossref_primary_10_1007_s11590_018_1240_3 crossref_primary_10_1016_j_swevo_2020_100762 crossref_primary_10_3390_app12136316 crossref_primary_10_1007_s11721_013_0076_9 crossref_primary_10_1007_s41604_019_00010_9 crossref_primary_10_1016_j_cma_2024_116915 crossref_primary_10_1155_2016_1510256 crossref_primary_10_1007_s11721_017_0131_z crossref_primary_10_1109_TEVC_2019_2921598 crossref_primary_10_3390_a9020023 crossref_primary_10_3390_sym10060210 crossref_primary_10_1007_s10489_021_02952_9 crossref_primary_10_1080_10407782_2019_1630241 crossref_primary_10_1134_S0005117921060011 crossref_primary_10_1016_j_cor_2014_05_020 |
| Cites_doi | 10.1007/s11721-007-0002-0 10.1137/S1052623493250780 10.4249/scholarpedia.1461 10.1016/S0167-739X(00)00043-1 10.1109/4235.985692 10.1109/3477.484436 10.1007/978-3-642-02538-9_13 10.1051/ita:2006009 10.1007/978-3-642-04244-7_14 10.1162/evco.2008.16.1.31 10.1007/0-387-30065-1_16 10.1007/b99492 10.1007/3-540-32494-1_4 10.1145/1569901.1569940 10.1287/opre.1050.0243 10.1002/9780470612163 10.1162/1063656054794815 10.1109/4235.585892 10.1109/TSMCC.2006.875410 10.4249/scholarpedia.1486 10.1016/j.artint.2007.09.010 10.1007/978-3-642-00483-4 10.1109/ICNN.1995.488968 10.1023/B:ANOR.0000039526.52305.af 10.1137/040603371 10.1109/CI-M.2006.248054 10.1613/jair.2861 10.1007/3540634932_27 |
| ContentType | Journal Article |
| Copyright | Springer Science + Business Media, LLC 2011 |
| Copyright_xml | – notice: Springer Science + Business Media, LLC 2011 |
| DBID | AAYXX CITATION |
| DOI | 10.1007/s11721-011-0065-9 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1935-3820 |
| EndPage | 75 |
| ExternalDocumentID | 10_1007_s11721_011_0065_9 |
| GroupedDBID | -5B -5G -BR -D3 -DT -EM -Y2 -~C .86 .VR 06D 0R~ 0VY 123 1N0 203 29Q 2J2 2JN 2JY 2KG 2KM 2LR 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5VS 67Z 6NX 875 8TC 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBXA ABDZT ABECU ABFTD ABFTV ABHQN ABJNI ABJOX ABKCH ABMNI ABMQK ABNWP ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACDTI ACGFO ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACPRK ACREN ACSNA ACZOJ ADHHG ADHIR ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEBTG AEFQL AEGAL AEGNC AEJHL AEJRE AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFGCZ AFKRA AFLOW AFQWF AFWTZ AFYQB AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARMRJ AXYYD AYJHY B-. BA0 BBNVY BDATZ BENPR BGNMA BHPHI BSONS CAG CCPQU COF CS3 CSCUP DDRTE DNIVK DPUIP DU5 EBLON EBS EIOEI EJD ESBYG FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HLICF HMJXF HQYDN HRMNR HZ~ IJ- IKXTQ IWAJR IXD IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KOV KZ1 LLZTM M4Y M7P MA- NPVJJ NQJWS NU0 O9- O93 O9J OAM P2P P9P PF0 PT4 QOS R89 R9I RIG ROL RPX RSV S16 S1Z S27 S3B SAP SDH SEG SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z7R Z7X Z83 Z88 ZMTXR ~A9 AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC AEZWR AFDZB AFFHD AFHIU AFOHR AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PQGLB |
| ID | FETCH-LOGICAL-c288t-3b759051e0bc44387d38b5e4a2d6a8b8f8b2a3081c74247d9789babb475c56f13 |
| IEDL.DBID | RSV |
| ISICitedReferencesCount | 39 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000298863800003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1935-3812 |
| IngestDate | Sat Nov 29 01:34:25 EST 2025 Tue Nov 18 21:51:18 EST 2025 Fri Feb 21 02:33:22 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | Swarm intelligence F-Race Automated algorithm configuration Parameter tuning Continuous optimization algorithm |
| Language | English |
| License | http://www.springer.com/tdm |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c288t-3b759051e0bc44387d38b5e4a2d6a8b8f8b2a3081c74247d9789babb475c56f13 |
| PageCount | 27 |
| ParticipantIDs | crossref_primary_10_1007_s11721_011_0065_9 crossref_citationtrail_10_1007_s11721_011_0065_9 springer_journals_10_1007_s11721_011_0065_9 |
| PublicationCentury | 2000 |
| PublicationDate | 2012-03-01 |
| PublicationDateYYYYMMDD | 2012-03-01 |
| PublicationDate_xml | – month: 03 year: 2012 text: 2012-03-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Boston |
| PublicationPlace_xml | – name: Boston |
| PublicationTitle | Swarm intelligence |
| PublicationTitleAbbrev | Swarm Intell |
| PublicationYear | 2012 |
| Publisher | Springer US |
| Publisher_xml | – name: Springer US |
| References | Auger, Hansen, Zerpa, Ros, Schoenauer, Vahrenhold (CR4) 2009 Dorigo, Maniezzo, Colorni (CR15) 1996; 26 Audet, Dennis (CR3) 2006; 17 Birattari, Zlochin, Dorigo (CR8) 2006; 40 Ansótegui, Sellmann, Tierney, Gent (CR2) 2009 Poli, Kennedy, Blackwell (CR30) 2007; 1 Birattari, Stützle, Paquete, Varrentrapp, Langdon (CR7) 2002 CR35 Birattari, Yuan, Balaprakash, Stützle, Bartz-Beielstein (CR9) 2010 Bartz-Beielstein (CR5) 2006 CR32 Dorigo, Stützle (CR14) 2004 Nannen, Eiben (CR28) 2007 Torczon (CR38) 1997; 7 Birattari (CR6) 2009 Kennedy, Eberhart, Shi (CR26) 2001 Powell (CR31) 2006 Adenso-Díaz, Laguna (CR1) 2006; 54 Fukunaga (CR18) 2008; 16 Steinmann, Strohmaier, Stützle, Brewka, Habel, Nebel (CR33) 1997 Jones, Forrest, Eshelman (CR23) 1995 Kennedy, Eberhart (CR24) 1995 Zlochin, Birattari, Meuleau, Dorigo (CR41) 2004; 131 Stützle, Hoos (CR37) 2000; 16 Stützle (CR34) 1999 Stützle, Hoos, Voss (CR36) 1998 Clerc, Kennedy (CR11) 2002; 6 CR22 Dorigo, Gambardella (CR13) 1997; 1 Hutter, Hoos, Leyton-Brown, Stützle (CR21) 2009; 36 Oltean (CR29) 2005; 13 Hansen, Lozano (CR19) 2006 Clerc (CR10) 2006 Dorigo (CR12) 2007; 2 Hutter, Hoos, Leyton-Brown, Murphy, Rothlauf (CR20) 2009 Yuan, Montes de Oca, Birattari, Stützle, Dorigo (CR39) 2010 Dorigo, Montes de Oca, Engelbrecht (CR17) 2008; 3 Mengshoel (CR27) 2008; 172 Dorigo, Birattari, Stutzle (CR16) 2006; 1 Kennedy, Mendes (CR25) 2006; 36 Yuan, Stützle, Birattari, Ali (CR40) 2010 M. Dorigo (65_CR17) 2008; 3 T. Bartz-Beielstein (65_CR5) 2006 M. Dorigo (65_CR12) 2007; 2 65_CR35 F. Hutter (65_CR21) 2009; 36 M. Birattari (65_CR8) 2006; 40 J. Kennedy (65_CR26) 2001 V. Nannen (65_CR28) 2007 M. Clerc (65_CR10) 2006 N. Hansen (65_CR19) 2006 M. J. D. Powell (65_CR31) 2006 65_CR32 M. Dorigo (65_CR13) 1997; 1 M. Dorigo (65_CR14) 2004 M. Birattari (65_CR9) 2010 A. S. Fukunaga (65_CR18) 2008; 16 V. Torczon (65_CR38) 1997; 7 C. Audet (65_CR3) 2006; 17 A. Auger (65_CR4) 2009 O. Steinmann (65_CR33) 1997 T. Stützle (65_CR37) 2000; 16 J. Kennedy (65_CR24) 1995 T. Stützle (65_CR34) 1999 J. Kennedy (65_CR25) 2006; 36 T. Jones (65_CR23) 1995 T. Stützle (65_CR36) 1998 B. Adenso-Díaz (65_CR1) 2006; 54 Z. Yuan (65_CR40) 2010 O. Mengshoel (65_CR27) 2008; 172 M. Oltean (65_CR29) 2005; 13 M. Zlochin (65_CR41) 2004; 131 C. Ansótegui (65_CR2) 2009 M. Birattari (65_CR6) 2009 M. Birattari (65_CR7) 2002 M. Dorigo (65_CR16) 2006; 1 R. Poli (65_CR30) 2007; 1 Z. Yuan (65_CR39) 2010 65_CR22 M. Dorigo (65_CR15) 1996; 26 M. Clerc (65_CR11) 2002; 6 F. Hutter (65_CR20) 2009 |
| References_xml | – volume: 1 start-page: 33 issue: 1 year: 2007 end-page: 57 ident: CR30 article-title: Particle swarm optimization. An overview publication-title: Swarm Intelligence doi: 10.1007/s11721-007-0002-0 – volume: 7 start-page: 1 issue: 1 year: 1997 end-page: 25 ident: CR38 article-title: On the convergence of pattern search algorithms publication-title: SIAM Journal on Optimization doi: 10.1137/S1052623493250780 – ident: CR22 – volume: 2 start-page: 1461 issue: 3 year: 2007 ident: CR12 article-title: Ant colony optimization publication-title: Scholarpedia doi: 10.4249/scholarpedia.1461 – volume: 16 start-page: 889 issue: 8 year: 2000 end-page: 914 ident: CR37 article-title: – ant system publication-title: Future Generations Computer Systems doi: 10.1016/S0167-739X(00)00043-1 – volume: 6 start-page: 58 issue: 1 year: 2002 end-page: 73 ident: CR11 article-title: The particle swarm–explosion, stability, and convergence in a multidimensional complex space publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.985692 – volume: 26 start-page: 29 issue: 1 year: 1996 end-page: 41 ident: CR15 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Transactions on Systems, Man and Cybernetics. Part B. Cybernetics doi: 10.1109/3477.484436 – year: 2001 ident: CR26 publication-title: Swarm intelligence – start-page: 311 year: 2010 end-page: 336 ident: CR9 article-title: F-Race and iterated F-Race: An overview publication-title: Experimental methods for the analysis of optimization algorithms doi: 10.1007/978-3-642-02538-9_13 – volume: 40 start-page: 353 issue: 2 year: 2006 end-page: 369 ident: CR8 article-title: Towards a theory of practice in metaheuristics design: a machine learning perspective publication-title: Theoretical Informatics and Applications doi: 10.1051/ita:2006009 – start-page: 142 year: 2009 end-page: 157 ident: CR2 article-title: A gender-based genetic algorithm for the automatic configuration of solvers publication-title: Principles and practice of constraint programming—CP 2009 doi: 10.1007/978-3-642-04244-7_14 – volume: 36 start-page: 267 year: 2009 end-page: 306 ident: CR21 article-title: ParamILS: an automatic algorithm configuration framework publication-title: Journal of Artificial Intelligence Research – ident: CR35 – start-page: 3 year: 2009 end-page: 15 ident: CR4 article-title: Experimental comparisons of derivative free optimization algorithms publication-title: Experimental algorithms, 8th international symposium, SEA 2009 – start-page: 975 year: 2007 end-page: 980 ident: CR28 article-title: Relevance estimation and value calibration of evolutionary algorithm parameters publication-title: Proc. of IJCAI 2007 – volume: 16 start-page: 31 issue: 1 year: 2008 end-page: 61 ident: CR18 article-title: Automated discovery of local search heuristics for satisfiability testing publication-title: Evolutionary Computation doi: 10.1162/evco.2008.16.1.31 – year: 1999 ident: CR34 publication-title: Local search algorithms for combinatorial problems: analysis, improvements, and new applications – start-page: 255 year: 2006 end-page: 297 ident: CR31 article-title: The NEWUOA software for unconstrained optimization publication-title: Large-scale nonlinear optimization doi: 10.1007/0-387-30065-1_16 – year: 2004 ident: CR14 publication-title: Ant colony optimization doi: 10.1007/b99492 – start-page: 75 year: 2006 end-page: 102 ident: CR19 article-title: The CMA evolution strategy: a comparing review publication-title: Towards a new evolutionary computation doi: 10.1007/3-540-32494-1_4 – start-page: 271 year: 2009 end-page: 278 ident: CR20 article-title: An experimental investigation of model-based parameter optimisation: SPO and beyond publication-title: Genetic and evolutionary computation conference, GECCO 2009 doi: 10.1145/1569901.1569940 – volume: 54 start-page: 99 issue: 1 year: 2006 end-page: 114 ident: CR1 article-title: Fine-tuning of algorithms using fractional experimental designs and local search publication-title: Operations Research doi: 10.1287/opre.1050.0243 – volume: 1 start-page: 28 issue: 4 year: 2006 end-page: 39 ident: CR16 article-title: Ant colony optimization publication-title: IEEE Computational Intelligence Magazine – start-page: 337 year: 1997 end-page: 348 ident: CR33 article-title: Tabu search vs. random walk publication-title: KI-97: advances in artificial intelligence – start-page: 204 year: 2010 end-page: 215 ident: CR39 article-title: Modern continuous optimization algorithms for tuning real and integer algorithm parameters publication-title: Proceedings of ANTS 2010, the seventh international conference on swarm intelligence – start-page: 184 year: 1995 end-page: 192 ident: CR23 article-title: Fitness distance correlation as a measure of problem difficulty for genetic algorithms publication-title: Proc. of the 6th international conference on genetic algorithms – year: 2006 ident: CR10 publication-title: Particle swarm optimization doi: 10.1002/9780470612163 – year: 2006 ident: CR5 publication-title: Experimental research in evolutionary computation–the new experimentalism – start-page: 11 year: 2002 end-page: 18 ident: CR7 article-title: A racing algorithm for configuring metaheuristics publication-title: GECCO 2002: proceedings of the genetic and evolutionary computation conference – volume: 13 start-page: 387 issue: 3 year: 2005 end-page: 410 ident: CR29 article-title: Evolving evolutionary algorithms using linear genetic programming publication-title: Evolutionary Computation doi: 10.1162/1063656054794815 – volume: 1 start-page: 53 issue: 1 year: 1997 end-page: 66 ident: CR13 article-title: Ant colony system: a cooperative learning approach to the traveling salesman problem publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.585892 – volume: 36 start-page: 515 issue: 4 year: 2006 end-page: 519 ident: CR25 article-title: Neighborhood topologies in fully informed and best-of-neighborhood particle swarms publication-title: IEEE Transactions on Systems, Man and Cybernetics. Part C, Applications and Reviews doi: 10.1109/TSMCC.2006.875410 – ident: CR32 – start-page: 313 year: 1998 end-page: 329 ident: CR36 article-title: MAX-MIN ant system and local search for combinatorial optimization problems: Towards adaptive tools for combinatorial global optimization publication-title: Meta-heuristics: advances and trends in local search paradigms for optimization – volume: 3 start-page: 1486 issue: 11 year: 2008 ident: CR17 article-title: Particle swarm optimization publication-title: Scholarpedia doi: 10.4249/scholarpedia.1486 – start-page: 41 year: 2010 end-page: 50 ident: CR40 article-title: MADS/F-Race: mesh adaptive direct search meets F-race publication-title: Proceedings of IEA-AIE 2010 – volume: 172 start-page: 955 issue: 8–9 year: 2008 end-page: 990 ident: CR27 article-title: Understanding the role of noise in stochastic local search: analysis and experiments publication-title: Artificial Intelligence doi: 10.1016/j.artint.2007.09.010 – year: 2009 ident: CR6 publication-title: Tuning metaheuristics: a machine learning perspective doi: 10.1007/978-3-642-00483-4 – start-page: 1942 year: 1995 end-page: 1948 ident: CR24 article-title: Particle swarm optimization publication-title: Proc. of IEEE international conference on neural networks doi: 10.1109/ICNN.1995.488968 – volume: 131 start-page: 373 issue: 1–4 year: 2004 end-page: 395 ident: CR41 article-title: Model-based search for combinatorial optimization: a critical survey publication-title: Annals of Operations Research doi: 10.1023/B:ANOR.0000039526.52305.af – volume: 17 start-page: 188 issue: 1 year: 2006 end-page: 217 ident: CR3 article-title: Mesh adaptive direct search algorithms for constrained optimization publication-title: SIAM Journal on Optimization doi: 10.1137/040603371 – start-page: 142 volume-title: Principles and practice of constraint programming—CP 2009 year: 2009 ident: 65_CR2 doi: 10.1007/978-3-642-04244-7_14 – start-page: 184 volume-title: Proc. of the 6th international conference on genetic algorithms year: 1995 ident: 65_CR23 – volume: 13 start-page: 387 issue: 3 year: 2005 ident: 65_CR29 publication-title: Evolutionary Computation doi: 10.1162/1063656054794815 – start-page: 204 volume-title: Proceedings of ANTS 2010, the seventh international conference on swarm intelligence year: 2010 ident: 65_CR39 – ident: 65_CR22 – volume: 17 start-page: 188 issue: 1 year: 2006 ident: 65_CR3 publication-title: SIAM Journal on Optimization doi: 10.1137/040603371 – start-page: 975 volume-title: Proc. of IJCAI 2007 year: 2007 ident: 65_CR28 – volume-title: Experimental research in evolutionary computation–the new experimentalism year: 2006 ident: 65_CR5 – volume: 1 start-page: 53 issue: 1 year: 1997 ident: 65_CR13 publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.585892 – volume: 1 start-page: 28 issue: 4 year: 2006 ident: 65_CR16 publication-title: IEEE Computational Intelligence Magazine doi: 10.1109/CI-M.2006.248054 – volume-title: Swarm intelligence year: 2001 ident: 65_CR26 – volume: 36 start-page: 515 issue: 4 year: 2006 ident: 65_CR25 publication-title: IEEE Transactions on Systems, Man and Cybernetics. Part C, Applications and Reviews doi: 10.1109/TSMCC.2006.875410 – start-page: 1942 volume-title: Proc. of IEEE international conference on neural networks year: 1995 ident: 65_CR24 doi: 10.1109/ICNN.1995.488968 – volume: 40 start-page: 353 issue: 2 year: 2006 ident: 65_CR8 publication-title: Theoretical Informatics and Applications doi: 10.1051/ita:2006009 – volume-title: Ant colony optimization year: 2004 ident: 65_CR14 doi: 10.1007/b99492 – start-page: 271 volume-title: Genetic and evolutionary computation conference, GECCO 2009 year: 2009 ident: 65_CR20 doi: 10.1145/1569901.1569940 – ident: 65_CR32 – start-page: 75 volume-title: Towards a new evolutionary computation year: 2006 ident: 65_CR19 doi: 10.1007/3-540-32494-1_4 – volume: 16 start-page: 31 issue: 1 year: 2008 ident: 65_CR18 publication-title: Evolutionary Computation doi: 10.1162/evco.2008.16.1.31 – start-page: 41 volume-title: Proceedings of IEA-AIE 2010 year: 2010 ident: 65_CR40 – volume-title: Local search algorithms for combinatorial problems: analysis, improvements, and new applications year: 1999 ident: 65_CR34 – start-page: 313 volume-title: Meta-heuristics: advances and trends in local search paradigms for optimization year: 1998 ident: 65_CR36 – volume: 6 start-page: 58 issue: 1 year: 2002 ident: 65_CR11 publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.985692 – volume: 16 start-page: 889 issue: 8 year: 2000 ident: 65_CR37 publication-title: Future Generations Computer Systems doi: 10.1016/S0167-739X(00)00043-1 – volume: 3 start-page: 1486 issue: 11 year: 2008 ident: 65_CR17 publication-title: Scholarpedia doi: 10.4249/scholarpedia.1486 – volume: 1 start-page: 33 issue: 1 year: 2007 ident: 65_CR30 publication-title: Swarm Intelligence doi: 10.1007/s11721-007-0002-0 – volume-title: Particle swarm optimization year: 2006 ident: 65_CR10 doi: 10.1002/9780470612163 – start-page: 11 volume-title: GECCO 2002: proceedings of the genetic and evolutionary computation conference year: 2002 ident: 65_CR7 – ident: 65_CR35 – start-page: 311 volume-title: Experimental methods for the analysis of optimization algorithms year: 2010 ident: 65_CR9 doi: 10.1007/978-3-642-02538-9_13 – volume: 26 start-page: 29 issue: 1 year: 1996 ident: 65_CR15 publication-title: IEEE Transactions on Systems, Man and Cybernetics. Part B. Cybernetics doi: 10.1109/3477.484436 – volume: 172 start-page: 955 issue: 8–9 year: 2008 ident: 65_CR27 publication-title: Artificial Intelligence doi: 10.1016/j.artint.2007.09.010 – volume: 131 start-page: 373 issue: 1–4 year: 2004 ident: 65_CR41 publication-title: Annals of Operations Research doi: 10.1023/B:ANOR.0000039526.52305.af – volume: 7 start-page: 1 issue: 1 year: 1997 ident: 65_CR38 publication-title: SIAM Journal on Optimization doi: 10.1137/S1052623493250780 – volume-title: Tuning metaheuristics: a machine learning perspective year: 2009 ident: 65_CR6 doi: 10.1007/978-3-642-00483-4 – volume: 36 start-page: 267 year: 2009 ident: 65_CR21 publication-title: Journal of Artificial Intelligence Research doi: 10.1613/jair.2861 – volume: 54 start-page: 99 issue: 1 year: 2006 ident: 65_CR1 publication-title: Operations Research doi: 10.1287/opre.1050.0243 – start-page: 337 volume-title: KI-97: advances in artificial intelligence year: 1997 ident: 65_CR33 doi: 10.1007/3540634932_27 – start-page: 255 volume-title: Large-scale nonlinear optimization year: 2006 ident: 65_CR31 doi: 10.1007/0-387-30065-1_16 – start-page: 3 volume-title: Experimental algorithms, 8th international symposium, SEA 2009 year: 2009 ident: 65_CR4 – volume: 2 start-page: 1461 issue: 3 year: 2007 ident: 65_CR12 publication-title: Scholarpedia doi: 10.4249/scholarpedia.1461 |
| SSID | ssj0059333 |
| Score | 2.1280072 |
| Snippet | The performance of optimization algorithms, including those based on swarm intelligence, depends on the values assigned to their parameters. To obtain high... |
| SourceID | crossref springer |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 49 |
| SubjectTerms | Artificial Intelligence Communications Engineering Computer Communication Networks Computer Science Computer Systems Organization and Communication Networks Mathematical and Computational Engineering Networks |
| Title | Continuous optimization algorithms for tuning real and integer parameters of swarm intelligence algorithms |
| URI | https://link.springer.com/article/10.1007/s11721-011-0065-9 |
| Volume | 6 |
| WOSCitedRecordID | wos000298863800003&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: Springer LINK customDbUrl: eissn: 1935-3820 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0059333 issn: 1935-3812 databaseCode: RSV dateStart: 20070601 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/eLvHCXMwnV07T8MwED5BYWChPEV5yQMTyFJwnNgZEaJiqhAvdYvsxIGiNkVJCn-fcxJTKgESzDlb0dm-7x72dwAnGlFNellEw9SmbhCQaCQNo0ak6I-cC1xpWTebEIOBHA6jm_Ydd-luu7uSZG2p54_dbLRC65Qe4iaNlmEF0U7a03h79-jMb4ARut-UkgOKcMRcKfO7KRbBaLESWgNMv_uvX9uA9dafJBfNBtiEJZNvQdf1aiDt0d2GF0tDNcpnGOiTKZqJSfv-kqjx07QYVc-TkqD_SqqZTZQQdCXHROUpqekkcCJLET6xV2dweEbKd1VM6m-OzvPLPDvw0L-6v7ymbZ8FmjApK-prEViaLuPphHNfitSXOjBcsTRUUstMaqZ89B0SjKO5SDHwjLTSmosgCcLs3N-FTj7NzR6QkKMoE3YM55lQ0iQpw4gs8FQYcaZ64DmFx0lLQm57YYzjOX2y1WWMuoytLuOoB6efQ14bBo7fhM_cCsXtYSx_lt7_k_QBrKG3xJoLaIfQqYqZOYLV5K0alcVxvQk_AMYg1rQ |
| linkProvider | Springer Nature |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dS8MwEA86BX1xfuL8zINPSqBL0yZ9FHFMnEN0yt5K0g-drJ20nf77XtrGOVBBn3sJ5fLxu8vd_Q6hEwWoJqzYI26on24AkIgnIkoiHoI90uaw0qJsNsH7fTEcerd1HXdust1NSLK8qWfFbtpbIeWTHuAm8RbREgPA0nl8d_eP5vp1wEO3q1CyQwCOqAllfjfFPBjNR0JLgOk0__Vr62ittifxebUBNtBClG6ipunVgOuju4VeNA3VKJ2Co48ncE0kdf0lluOnSTYqnpMcg_2Ki6l-KMFgSo6xTENc0knARJoiPNGpMzA8xvm7zJLym6Hz_DLPNnroXA4uuqTus0ACKkRBbMUdTdMVWSpgzBY8tIVyIiZp6EqhRCwUlTbYDgH40YyH4Hh6SirFuBM4bty2d1AjnaTRLsIuA1HK9RjGYi5FFIQUPDLHkq7HqGwhyyjcD2oSct0LY-zP6JO1Ln3Qpa916XstdPo55LVi4PhN-MyskF8fxvxn6b0_SR-jle7gpuf3rvrX-2gVLCdaJaMdoEaRTaNDtBy8FaM8Oyo35AfgEdmY |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1JS8NAFB60inixrljXOXhShqaTSWZyFLUoSim40FuYyaKVJilZ9O_7Jou1oIJ4zptHeLO8_XsInSjQasIIHWL7OnQDCok4IqAk4D7YIz0OOy3KYRN8MBCjkTOs55xmTbV7k5Kseho0SlOcd6d-2J01vmnPhZThPdChxFlES0zPDNLu-v1T8xRb4K2bVVrZIqCaaJPW_I7FvGKaz4qWyqbf_vdvrqO12s7E59XB2EALQbyJ2s0MB1xf6S30quGpxnGRFBlO4PmI6r5MLCfPSTrOX6IMg12L80IHUDCYmBMsYx-XMBPASEOHR7qkBpaHOHuXaVR-a2A-v_DZRo_9q4eLa1LPXyAeFSInpuKWhu8KDOUxZgrum0JZAZPUt6VQIhSKShNsCg_8a8Z9cEgdJZVi3PIsO-yZO6gVJ3Gwi7DNgJRyvYaxkEsReD4FT80ypO0wKjvIaITvejU4uZ6RMXFnsMpali7I0tWydJ0OOv1cMq2QOX4jPmt2y60vafYz9d6fqI_RyvCy797dDG730SoYVLSqUTtArTwtgkO07L3l4yw9Ks_mB3Ni4nw |
| 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=Continuous+optimization+algorithms+for+tuning+real+and+integer+parameters+of+swarm+intelligence+algorithms&rft.jtitle=Swarm+intelligence&rft.au=Yuan%2C+Zhi&rft.au=Montes%C2%A0de%C2%A0Oca%2C+Marco+A.&rft.au=Birattari%2C+Mauro&rft.au=St%C3%BCtzle%2C+Thomas&rft.date=2012-03-01&rft.pub=Springer+US&rft.issn=1935-3812&rft.eissn=1935-3820&rft.volume=6&rft.issue=1&rft.spage=49&rft.epage=75&rft_id=info:doi/10.1007%2Fs11721-011-0065-9&rft.externalDocID=10_1007_s11721_011_0065_9 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1935-3812&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1935-3812&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1935-3812&client=summon |