A novel binary artificial bee colony algorithm based on genetic operators
This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve binary optimization problems. Integrated to the neighbourhood searching mechanism of the basic ABC algorithm, the modification comprises four stag...
Saved in:
| Published in: | Information sciences Vol. 297; pp. 154 - 170 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
10.03.2015
|
| Subjects: | |
| ISSN: | 0020-0255 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve binary optimization problems. Integrated to the neighbourhood searching mechanism of the basic ABC algorithm, the modification comprises four stages: (1) In neighbourhood of a (current) food source, randomly select two food sources from population and generate a solution including zeros (Zero) outside the population; (2) apply two-point crossover operator between the current, two neighbourhood, global best and Zero food sources to create children food sources; (3) apply swap operator to the children food sources to generate grandchildren food sources; and (4) select the best food source as a neighbourhood food source of the current solution among the children and grandchildren food sources. In this way, the global–local search ability of the basic ABC algorithm is improved in binary domain. The effectiveness of the proposed algorithm GB-ABC is tested on two well-known binary optimization problems: dynamic image clustering and 0–1 knapsack problems. The obtained results clearly indicate that GB-ABC is the most suitable algorithm in binary optimization when compared with the other well-known existing binary optimization algorithms. In addition, the achievement of the proposed algorithm is supported by applying it to the CEC2005 benchmark numerical problems. |
|---|---|
| AbstractList | This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve binary optimization problems. Integrated to the neighbourhood searching mechanism of the basic ABC algorithm, the modification comprises four stages: (1) In neighbourhood of a (current) food source, randomly select two food sources from population and generate a solution including zeros (Zero) outside the population; (2) apply two-point crossover operator between the current, two neighbourhood, global best and Zero food sources to create children food sources; (3) apply swap operator to the children food sources to generate grandchildren food sources; and (4) select the best food source as a neighbourhood food source of the current solution among the children and grandchildren food sources. In this way, the global–local search ability of the basic ABC algorithm is improved in binary domain. The effectiveness of the proposed algorithm GB-ABC is tested on two well-known binary optimization problems: dynamic image clustering and 0–1 knapsack problems. The obtained results clearly indicate that GB-ABC is the most suitable algorithm in binary optimization when compared with the other well-known existing binary optimization algorithms. In addition, the achievement of the proposed algorithm is supported by applying it to the CEC2005 benchmark numerical problems. |
| Author | Karaboga, Dervis Ozturk, Celal Hancer, Emrah |
| Author_xml | – sequence: 1 givenname: Celal surname: Ozturk fullname: Ozturk, Celal email: celal@erciyes.edu.tr – sequence: 2 givenname: Emrah surname: Hancer fullname: Hancer, Emrah email: emrahhancer@erciyes.edu.tr – sequence: 3 givenname: Dervis surname: Karaboga fullname: Karaboga, Dervis email: karaboga@erciyes.edu.tr |
| BookMark | eNp9kD1vwjAQhj1QqUD7A7pl7EJ6jolD1AmhfklIXdrZci5nahRsahuk_vsa0akD0-levc9J90zYyHlHjN1xKDlw-bAtrYtlBXye9xIkjNgYoIIZVHV9zSYxbgFg3kg5Zm_LwvkjDUVnnQ4_hQ7JGotW54SoQD94l9Nh44NNX7ui05H6wrtiQ46SxcLvKejkQ7xhV0YPkW7_5pR9Pj99rF5n6_eXt9VyPUMhIM1aDQusDXTzXkokg4b3taz1QoNouOhbUzckjJF8gVp3dSOwarAVJFrDEToxZffnu_vgvw8Uk9rZiDQM2pE_RMWlBGjatqpztTlXMfgYAxmFNulkvUtB20FxUCdhaquyMHUSdoqysEzyf-Q-2F0WdJF5PDOUvz9aCiqiJYfU20CYVO_tBfoXLAOIbw |
| CitedBy_id | crossref_primary_10_1016_j_ijleo_2016_09_085 crossref_primary_10_1109_ACCESS_2021_3124710 crossref_primary_10_1016_j_ins_2018_02_025 crossref_primary_10_1016_j_engappai_2025_110464 crossref_primary_10_1016_j_swevo_2016_06_004 crossref_primary_10_1007_s00500_023_08491_4 crossref_primary_10_1007_s10845_017_1313_7 crossref_primary_10_1016_j_knosys_2017_04_015 crossref_primary_10_1007_s00500_017_2485_y crossref_primary_10_1016_j_future_2018_06_054 crossref_primary_10_1016_j_jksuci_2018_09_017 crossref_primary_10_3390_sym13030419 crossref_primary_10_1007_s00500_021_06613_4 crossref_primary_10_1007_s00500_017_2539_1 crossref_primary_10_1109_TFUZZ_2020_2973123 crossref_primary_10_1016_j_adhoc_2016_06_009 crossref_primary_10_1016_j_eswa_2019_03_039 crossref_primary_10_1016_j_jestch_2025_102057 crossref_primary_10_1016_j_ins_2019_10_029 crossref_primary_10_1016_j_asoc_2020_106799 crossref_primary_10_1016_j_asoc_2016_04_019 crossref_primary_10_1007_s13042_020_01165_9 crossref_primary_10_1155_2021_6648650 crossref_primary_10_1016_j_ins_2017_11_007 crossref_primary_10_1016_j_ins_2019_07_022 crossref_primary_10_3390_sym12081222 crossref_primary_10_1007_s10489_021_02611_z crossref_primary_10_1016_j_asoc_2022_109590 crossref_primary_10_1051_matecconf_201817302002 crossref_primary_10_1016_j_asoc_2018_01_001 crossref_primary_10_3390_sym11070876 crossref_primary_10_1016_j_eswa_2020_113717 crossref_primary_10_1155_2017_6043109 crossref_primary_10_1007_s00357_018_9270_1 crossref_primary_10_1016_j_phycom_2017_06_003 crossref_primary_10_3390_a15010024 crossref_primary_10_1002_cpe_5218 crossref_primary_10_1080_0305215X_2019_1657113 crossref_primary_10_1016_j_swevo_2024_101567 crossref_primary_10_1177_09544062241288633 crossref_primary_10_4018_JITR_2019010107 crossref_primary_10_1007_s00371_021_02367_0 crossref_primary_10_1016_j_eswa_2021_114817 crossref_primary_10_1109_ACCESS_2019_2942340 crossref_primary_10_1007_s00500_017_2689_1 crossref_primary_10_1016_j_ins_2015_08_004 crossref_primary_10_1007_s10586_024_04351_4 crossref_primary_10_1016_j_ins_2016_05_037 crossref_primary_10_4018_IJSIR_352061 crossref_primary_10_1007_s10489_017_1025_x crossref_primary_10_1016_j_epsr_2022_109094 crossref_primary_10_1016_j_ins_2016_03_023 crossref_primary_10_1016_j_future_2019_03_032 crossref_primary_10_1049_iet_gtd_2020_0729 crossref_primary_10_1007_s40747_020_00171_2 crossref_primary_10_1109_ACCESS_2021_3105796 crossref_primary_10_1016_j_asoc_2021_107351 crossref_primary_10_3233_JIFS_169079 crossref_primary_10_3233_ICA_200618 crossref_primary_10_1016_j_epsr_2019_105948 crossref_primary_10_1016_j_ins_2022_08_016 crossref_primary_10_1016_j_cie_2022_108605 crossref_primary_10_1016_j_swevo_2018_02_013 crossref_primary_10_1177_00368504211016205 crossref_primary_10_1098_rsos_221256 crossref_primary_10_1016_j_cie_2017_12_009 crossref_primary_10_1007_s00521_022_07969_w crossref_primary_10_1016_j_future_2017_05_044 crossref_primary_10_1007_s12351_018_0427_9 crossref_primary_10_1016_j_energy_2021_120790 crossref_primary_10_1016_j_ins_2018_01_026 crossref_primary_10_1016_j_cie_2023_109080 crossref_primary_10_1016_j_matcom_2025_03_019 crossref_primary_10_1016_j_ins_2015_08_014 crossref_primary_10_1007_s10586_016_0683_5 crossref_primary_10_1016_j_ins_2020_03_064 crossref_primary_10_1016_j_eswa_2019_113097 crossref_primary_10_1016_j_asoc_2016_12_017 crossref_primary_10_1007_s11227_019_03083_2 crossref_primary_10_1080_01969722_2018_1541597 crossref_primary_10_1109_TSC_2016_2612663 crossref_primary_10_1186_s13638_016_0802_2 crossref_primary_10_1002_er_8192 crossref_primary_10_1109_ACCESS_2022_3218685 crossref_primary_10_1016_j_ins_2016_07_022 crossref_primary_10_1016_j_asoc_2019_105576 crossref_primary_10_1016_j_eswa_2018_09_050 crossref_primary_10_3390_sym12060922 crossref_primary_10_1049_iet_ipr_2020_0111 crossref_primary_10_1016_j_asoc_2018_09_007 crossref_primary_10_1155_2021_5525602 crossref_primary_10_2166_hydro_2017_145 crossref_primary_10_1016_j_asoc_2020_107054 crossref_primary_10_1016_j_swevo_2019_01_003 crossref_primary_10_1016_j_ins_2017_08_067 crossref_primary_10_1007_s11042_024_20121_1 crossref_primary_10_1007_s00521_023_08358_7 crossref_primary_10_1016_j_heliyon_2023_e20867 crossref_primary_10_1155_2018_3407646 crossref_primary_10_1007_s00521_016_2348_y crossref_primary_10_1049_rsn2_70028 crossref_primary_10_1371_journal_pone_0274625 crossref_primary_10_1007_s00521_022_07058_y crossref_primary_10_1016_j_neucom_2016_12_037 crossref_primary_10_3390_math9182250 crossref_primary_10_1007_s00500_019_03785_y crossref_primary_10_1016_j_eswa_2023_120377 crossref_primary_10_1016_j_asoc_2021_107462 crossref_primary_10_1016_j_ins_2021_10_025 |
| Cites_doi | 10.1007/s11276-012-0438-z 10.4249/scholarpedia.1462 10.1016/j.asoc.2011.08.038 10.1109/SIS.2013.6615186 10.1080/01969727408546059 10.1007/978-3-642-16527-6_14 10.1109/TPAMI.1979.4766909 10.4249/scholarpedia.6915 10.1109/34.85677 10.1016/j.asoc.2007.12.008 10.1109/SIS.2011.5952562 10.3906/elk-1203-104 10.1109/91.227387 10.1016/j.ins.2010.07.015 10.1007/s10589-012-9521-8 10.1016/j.amc.2010.08.049 10.1016/j.ins.2012.01.021 10.1080/01969727308546047 10.1007/s10898-007-9149-x 10.1109/ELECO.2013.6713896 10.1109/TCYB.2014.2298916 10.1007/s10044-005-0015-5 10.1109/SIS.2005.1501641 10.3390/s110606056 10.1007/978-3-540-28646-2_8 10.1109/TPWRS.2010.2059716 10.1109/TEVC.2009.2012163 10.1016/S0167-8655(99)00056-2 10.1109/MHS.1995.494215 10.1007/s10044-014-0365-y 10.15388/Informatica.2014.25 10.1006/cviu.2001.0951 10.1007/s10044-004-0218-1 10.1016/j.asoc.2013.07.009 10.1007/s10462-009-9127-4 10.1109/TSMCA.2007.909595 10.1109/ICDM.2001.989517 10.1016/j.asoc.2011.05.039 10.1145/331499.331504 10.1016/j.asoc.2009.12.025 10.1007/s10462-012-9328-0 10.1007/s11269-005-9001-3 10.1016/j.swevo.2011.11.003 10.1109/MCI.2010.936309 10.1016/j.asoc.2007.05.007 10.1109/CEC.2012.6252919 |
| ContentType | Journal Article |
| Copyright | 2014 Elsevier Inc. |
| Copyright_xml | – notice: 2014 Elsevier Inc. |
| DBID | AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D |
| DOI | 10.1016/j.ins.2014.10.060 |
| 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 | Computer and Information Systems Abstracts |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Library & Information Science |
| EndPage | 170 |
| ExternalDocumentID | 10_1016_j_ins_2014_10_060 S0020025514010536 |
| GroupedDBID | --K --M --Z -~X .DC .~1 0R~ 1B1 1RT 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AABNK AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AATTM AAXKI AAXUO AAYFN AAYWO ABAOU ABBOA ABFNM ABJNI ABMAC ABUCO ACDAQ ACGFS ACRLP ACVFH ACZNC ADBBV ADCNI ADEZE ADGUI ADTZH AEBSH AECPX AEIPS AEKER AENEX AEUPX AFPUW AFTJW AFXIZ AGCQF AGHFR AGRNS AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIGVJ AIIUN AIKHN AITUG AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU AOUOD APLSM ARUGR AXJTR BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFKBS EJD EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX IHE J1W JJJVA KOM LG9 LY1 M41 MHUIS MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SDP SES SPC SPCBC SSB SSD SSH SST SSV SSW SSZ T5K TN5 TWZ WH7 XPP ZMT ~02 ~G- 1OL 29I 77I 9DU AAAKG AAQXK AAYXX ABEFU ABWVN ABXDB ACLOT ACNNM ACRPL ADJOM ADMUD ADNMO ADVLN AFFNX AFJKZ AGQPQ AIGII APXCP ASPBG AVWKF AZFZN CITATION EFLBG FEDTE FGOYB HLZ HVGLF HZ~ H~9 R2- SBC SDS SEW UHS WUQ YYP ZY4 ~HD 7SC 8FD JQ2 L7M L~C L~D |
| ID | FETCH-LOGICAL-c330t-9a08c5f0b4d66cefcf1d565a8a03713d9f57e3ff618caab573c27c93e39f1c0b3 |
| ISICitedReferencesCount | 136 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000347862200008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0020-0255 |
| IngestDate | Sun Sep 28 04:28:55 EDT 2025 Sat Nov 29 07:58:11 EST 2025 Tue Nov 18 21:54:59 EST 2025 Fri Jul 18 18:51:56 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Artificial bee colony Dynamic clustering Binary optimization Genetic algorithm Knapsack problem |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c330t-9a08c5f0b4d66cefcf1d565a8a03713d9f57e3ff618caab573c27c93e39f1c0b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| PQID | 1660079925 |
| PQPubID | 23500 |
| PageCount | 17 |
| ParticipantIDs | proquest_miscellaneous_1660079925 crossref_citationtrail_10_1016_j_ins_2014_10_060 crossref_primary_10_1016_j_ins_2014_10_060 elsevier_sciencedirect_doi_10_1016_j_ins_2014_10_060 |
| PublicationCentury | 2000 |
| PublicationDate | 2015-03-10 |
| PublicationDateYYYYMMDD | 2015-03-10 |
| PublicationDate_xml | – month: 03 year: 2015 text: 2015-03-10 day: 10 |
| PublicationDecade | 2010 |
| PublicationTitle | Information sciences |
| PublicationYear | 2015 |
| Publisher | Elsevier Inc |
| Publisher_xml | – name: Elsevier Inc |
| References | Ma, Liang, Guo, Fan, Yin (b0220) 2011; 11 Bezdek (b0015) 1974; 3 L. Anne, X. Descombes, J. Zerubia, Fully unsupervised fuzzy clustering with entropy criterion, in: D. Xavier, Z. Josiane (Eds.), 15th International Conference on Pattern Recognition (ICPR’00), 2000, pp. 3998–3998. Omran, Salman, Engelbrecht (b0255) 2006; 8 Yew-Soon, Meng-Hiot, Xianshun (b0355) 2010; 5 Akay, Karaboga (b0005) 2012; 192 Bezdek (b0020) 1974 Kuo, Syu, Chen, Tien (b0210) 2012; 195 Haddad, Afshar, Mariño (b0110) 2006; 20 M. Omran, Particle Swarm Optimization Methods for Pattern Recognition and Image Processing, Ph.D. Thesis, University of Pretoria, Environment and Information Technology, 2004. Karaboga, Ozturk (b0175) 2011; 11 Raziuddin, Sattar, Lakshmi, Parvez (b0300) 2011 Magalhaes-Mendes (b0230) 2013; 12 Karaboga (b0140) 2010 Das, Biswas, Panigrahi, Kundu, Basu (b0070) 2014; 44 E. Zitzler, M. Laumanns, Test problems and test data for multiobjective optimizers, in: Systems Optimization, Test Problem Suite, ETH, Zurich, 2014. Das, Biswas, Kundu (b0065) 2013; 13 Karaboga, Okdem, Ozturk (b0165) 2012; 18 Wu, Fan (b0330) 2011 Karaboga, Basturk (b0150) 2007; 39 P. Lucic, D. Teodorovic, Bee system: modeling combinatorial optimization transportation engineering problems by swarm intelligence, in: Preprints of the TRISTAN IV Triennial Symposium on Transportation Analysis, Sao Miguel, Azores Islands, Portugal, 2001, pp. 441–445. Kellerer, Pferschy, Pisinger (b0190) 2004 Chou, Su, Lai (b0045) 2004; 7 Kashan, Nahavandi, Kashan (b0185) 2012; 12 Dawkins (b0085) 1976 S. Gordon, Unsupervised Image Clustering using Probabilistic Continuous Models and Information Theoretic Principles, Tel-Aviv University, Tel-Aviv 69978, Israel, 2006. Jain, Murty, Flynn (b0130) 1999; 31 . M. Dorigo, Optimization Learning and Natural Algorithms, Ph.D. Thesis, Politecnico Di Milano, Italy, 1992. Das, Abraham, Konar (b0055) 2008; 38 M. Halkidi, M. Vazirgiannis, Clustering validity assessment: finding the optimal partitioning of a data set, in: IEEE International Conference on Data Mining (ICDM 2001), San Jose, California, USA, 2001, pp. 187–194. Pham, Ghanbarzadeh, Koc, Otri, Rahim, Zaidi (b0285) 2005 Karaboga, Akay (b0145) 2009; 31 H. Wedde, M. Farooq, Y. Zhang, BeeHive: An Efficient Fault-Tolerant Routing Algorithm Inspired by Honey Bee Behavior, 2004, pp. 83–94. Millonas (b0235) 1994 J. MacQueen, Some methods for classification and analysis of multivariate observations, in: 5th Berkeley Symp. Math. Stat. Probability, 1967, pp. 281–297. Neri, Cotta (b0245) 2012; 2 Ozturk, Hancer, Karaboga (b0265) 2014; 25 Pham (b0290) 2001; 84 E. Hancer, C. Ozturk, D. Karaboga, Extraction of brain tumors from MRI images with artificial bee colony based segmentation methodology, in: ELECO’2013, Bursa, Turkiye, 2013. Z. Yan, Z. Chun-Guang, W. Sheng-Sheng, H. Lan, A dynamic clustering based on genetic algorithm, in: International Conference on Machine Learning and Cybernetics, vol. 221, 2003, pp. 222–224. Ozturk, Karaboga, Gorkemli (b0270) 2011; 11 R.H. Turi, Clustering-Based Colour Image Segmentation, Ph.D. Thesis, Monash University, Australia, 2001. Kohonen (b0200) 1995 Krishnapuram, Keller (b0205) 1993; 1 Calinski, Harabasz (b0040) 1974; 3 R. Eberhart, J. Kennedy, A new optimizer using particle swarm theory, in: 6th International Symposium on Micro Machine and Human Science, 1995. H. Wedde, M. Farooq, The wisdom of the hive applied to mobile ad-hoc networks, in: Swarm Intelligence Symposium SIS 2005, 2005, pp. 341–348. Chung, Han, Kit-Po (b0050) 2011; 26 C. Wallace, D. Dowe, Intrinsic classification by MML – the snob program, in: Seventh Australian Joint Conference on Artificial Intelligence, UNE, Armidale, NSW, Australia, 1994, pp. 37–44. Yang (b0350) 2005 E. Hancer, C. Ozturk, D. Karaboga, Artificial bee colony based image clustering method, in: IEEE Congress on Evolutionary Computation, CEC 2012, Brisbane, Australia, 2012, pp. 1–5. P.N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A. Auger, S. Tiwari, Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization, Nanyang Technological University, Singapore, IIT Kanpur, India, 2005. Karaboga, Ozturk (b0170) 2009; 19 Mukhopadhyay, Maulik, Bandyopadhyay (b0240) 2009; 13 Xu, Lei (b0340) 2010 Zhu, Kwong (b0360) 2010 Das, Konar (b0075) 2009; 9 Davies, Bouldin (b0080) 1979; 1 Karaboga, Gorkemli, Ozturk, Karaboga (b0160) 2014; 42 Birattari (b0025) 2007; 2 Kashan, Kashan, Nahavandi (b0180) 2013; 55 Kiran, Gunduz (b0195) 2013; 21 Ozturk, Hancer, Karaboga (b0260) 2014 Dunn (b0095) 1974; 4 S. Biswas, S. Kundu, D. Bose, S. Das, P.N. Suganthan, B.K. Panigrahi, Migrating forager population in a multi-population artificial bee colony algorithm with modified perturbation schemes, in: IEEE Symposium on Swarm Intelligence (SIS), 2013, pp. 248–255. D. Teodorovic, M. Dell’orco, Bee colony optimization – a cooperative learning approach to complex transportation problems, in: 16th mini-EURO Conference on Advanced OR and AI Methods in Transportation, 2005, pp. 51–60. Biswas, Das, Kundu, Patra (b0030) 2013; 18 D. Karaboga, An Idea based on Honey Bee Swarm for Numerical Optimization, Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005. G. Pampara, A.P. Engelbrecht, Binary artificial bee colony optimization, in: IEEE Symposium on Swarm Intelligence (SIS), 2011, pp. 1–8. Karaboga, Basturk (b0155) 2008; 8 J. Puzicha, T. Hofmann, J.M. Buhmann, Histogram Clustering for Unsupervised Image Segmentation, in: CVPR’99, 1999. Xie, Beni (b0335) 1991; 3 Das, Abraham, Konar (b0060) 2009 Wu (10.1016/j.ins.2014.10.060_b0330) 2011 Magalhaes-Mendes (10.1016/j.ins.2014.10.060_b0230) 2013; 12 Karaboga (10.1016/j.ins.2014.10.060_b0170) 2009; 19 10.1016/j.ins.2014.10.060_b0115 Dunn (10.1016/j.ins.2014.10.060_b0095) 1974; 4 Karaboga (10.1016/j.ins.2014.10.060_b0150) 2007; 39 Karaboga (10.1016/j.ins.2014.10.060_b0155) 2008; 8 Pham (10.1016/j.ins.2014.10.060_b0285) 2005 10.1016/j.ins.2014.10.060_b0315 Kashan (10.1016/j.ins.2014.10.060_b0185) 2012; 12 Kuo (10.1016/j.ins.2014.10.060_b0210) 2012; 195 Das (10.1016/j.ins.2014.10.060_b0075) 2009; 9 Das (10.1016/j.ins.2014.10.060_b0070) 2014; 44 Neri (10.1016/j.ins.2014.10.060_b0245) 2012; 2 10.1016/j.ins.2014.10.060_b0035 Calinski (10.1016/j.ins.2014.10.060_b0040) 1974; 3 10.1016/j.ins.2014.10.060_b0310 Pham (10.1016/j.ins.2014.10.060_b0290) 2001; 84 10.1016/j.ins.2014.10.060_b0275 Krishnapuram (10.1016/j.ins.2014.10.060_b0205) 1993; 1 10.1016/j.ins.2014.10.060_b0225 10.1016/j.ins.2014.10.060_b0105 Kashan (10.1016/j.ins.2014.10.060_b0180) 2013; 55 Dawkins (10.1016/j.ins.2014.10.060_b0085) 1976 10.1016/j.ins.2014.10.060_b0305 Karaboga (10.1016/j.ins.2014.10.060_b0175) 2011; 11 Karaboga (10.1016/j.ins.2014.10.060_b0165) 2012; 18 Kohonen (10.1016/j.ins.2014.10.060_b0200) 1995 Xie (10.1016/j.ins.2014.10.060_b0335) 1991; 3 Ozturk (10.1016/j.ins.2014.10.060_b0260) 2014 Chung (10.1016/j.ins.2014.10.060_b0050) 2011; 26 Akay (10.1016/j.ins.2014.10.060_b0005) 2012; 192 10.1016/j.ins.2014.10.060_b0100 Raziuddin (10.1016/j.ins.2014.10.060_b0300) 2011 Das (10.1016/j.ins.2014.10.060_b0055) 2008; 38 Haddad (10.1016/j.ins.2014.10.060_b0110) 2006; 20 10.1016/j.ins.2014.10.060_b0345 Yew-Soon (10.1016/j.ins.2014.10.060_b0355) 2010; 5 Jain (10.1016/j.ins.2014.10.060_b0130) 1999; 31 Kiran (10.1016/j.ins.2014.10.060_b0195) 2013; 21 Ma (10.1016/j.ins.2014.10.060_b0220) 2011; 11 Das (10.1016/j.ins.2014.10.060_b0065) 2013; 13 Birattari (10.1016/j.ins.2014.10.060_b0025) 2007; 2 10.1016/j.ins.2014.10.060_b0215 Kellerer (10.1016/j.ins.2014.10.060_b0190) 2004 Ozturk (10.1016/j.ins.2014.10.060_b0270) 2011; 11 Yang (10.1016/j.ins.2014.10.060_b0350) 2005 Biswas (10.1016/j.ins.2014.10.060_b0030) 2013; 18 Ozturk (10.1016/j.ins.2014.10.060_b0265) 2014; 25 10.1016/j.ins.2014.10.060_b0090 Millonas (10.1016/j.ins.2014.10.060_b0235) 1994 10.1016/j.ins.2014.10.060_b0135 Zhu (10.1016/j.ins.2014.10.060_b0360) 2010 Davies (10.1016/j.ins.2014.10.060_b0080) 1979; 1 10.1016/j.ins.2014.10.060_b0250 10.1016/j.ins.2014.10.060_b0295 10.1016/j.ins.2014.10.060_b0010 Xu (10.1016/j.ins.2014.10.060_b0340) 2010 Chou (10.1016/j.ins.2014.10.060_b0045) 2004; 7 10.1016/j.ins.2014.10.060_b0325 Karaboga (10.1016/j.ins.2014.10.060_b0140) 2010 10.1016/j.ins.2014.10.060_b0280 Karaboga (10.1016/j.ins.2014.10.060_b0160) 2014; 42 10.1016/j.ins.2014.10.060_b0320 Bezdek (10.1016/j.ins.2014.10.060_b0020) 1974 Mukhopadhyay (10.1016/j.ins.2014.10.060_b0240) 2009; 13 Omran (10.1016/j.ins.2014.10.060_b0255) 2006; 8 10.1016/j.ins.2014.10.060_b0365 10.1016/j.ins.2014.10.060_b0125 Karaboga (10.1016/j.ins.2014.10.060_b0145) 2009; 31 Bezdek (10.1016/j.ins.2014.10.060_b0015) 1974; 3 10.1016/j.ins.2014.10.060_b0120 Das (10.1016/j.ins.2014.10.060_b0060) 2009 |
| References_xml | – volume: 13 start-page: 4676 year: 2013 end-page: 4694 ident: b0065 article-title: Synergizing fitness learning with proximity-based food source selection in artificial bee colony algorithm for numerical optimization publication-title: Appl. Soft Comput. – volume: 18 start-page: 847 year: 2012 end-page: 860 ident: b0165 article-title: Cluster based wireless sensor network routing using artificial bee colony algorithm publication-title: Wireless Networks – volume: 9 start-page: 226 year: 2009 end-page: 236 ident: b0075 article-title: Automatic image pixel clustering with an improved differential evolution publication-title: Appl. Soft Comput. – volume: 12 start-page: 342 year: 2012 end-page: 352 ident: b0185 article-title: DisABC: a new artificial bee colony algorithm for binary optimization publication-title: Appl. Soft Comput. – year: 2004 ident: b0190 article-title: Knapsack Problems – volume: 195 start-page: 124 year: 2012 end-page: 140 ident: b0210 article-title: Integration of particle swarm optimization and genetic algorithm for dynamic clustering publication-title: Inform. Sci. – year: 2010 ident: b0360 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. – reference: S. Biswas, S. Kundu, D. Bose, S. Das, P.N. Suganthan, B.K. Panigrahi, Migrating forager population in a multi-population artificial bee colony algorithm with modified perturbation schemes, in: IEEE Symposium on Swarm Intelligence (SIS), 2013, pp. 248–255. – year: 1976 ident: b0085 article-title: The Selfish Gene – reference: R. Eberhart, J. Kennedy, A new optimizer using particle swarm theory, in: 6th International Symposium on Micro Machine and Human Science, 1995. – reference: M. Omran, Particle Swarm Optimization Methods for Pattern Recognition and Image Processing, Ph.D. Thesis, University of Pretoria, Environment and Information Technology, 2004. – volume: 84 start-page: 285 year: 2001 end-page: 297 ident: b0290 article-title: Spatial models for fuzzy clustering publication-title: Comput. Vis. Image Underst. – volume: 31 start-page: 61 year: 2009 end-page: 85 ident: b0145 article-title: A survey: algorithms simulating bee swarm intelligence publication-title: Artif. Intell. Rev. – year: 2005 ident: b0350 article-title: Engineering optimizations via nature-inspired virtual bee algorithms publication-title: Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach – volume: 38 start-page: 218 year: 2008 end-page: 237 ident: b0055 article-title: Automatic clustering using an improved differential evolution algorithm publication-title: IEEE Trans. Syst., Man Cybernet., Part A: Syst. Hum. – start-page: 51 year: 2011 end-page: 56 ident: b0330 article-title: Improved artificial bee colony algorithm with chaos publication-title: Computer science for Environmental Engineering and Ecoinformatics – volume: 44 start-page: 1884 year: 2014 end-page: 1897 ident: b0070 article-title: A spatially informative optic flow model of bee colony with saccadic flight strategy for global optimization publication-title: IEEE Trans. Cybernet. – volume: 31 start-page: 264 year: 1999 end-page: 323 ident: b0130 article-title: Data clustering: a review publication-title: ACM Comput. Surv. – year: 1994 ident: b0235 article-title: Swarms, Phase Transitions and Collective Intelligence – reference: M. Halkidi, M. Vazirgiannis, Clustering validity assessment: finding the optimal partitioning of a data set, in: IEEE International Conference on Data Mining (ICDM 2001), San Jose, California, USA, 2001, pp. 187–194. – reference: P.N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A. Auger, S. Tiwari, Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization, Nanyang Technological University, Singapore, IIT Kanpur, India, 2005. – volume: 192 start-page: 120 year: 2012 end-page: 142 ident: b0005 article-title: A modified artificial bee colony algorithm for real-parameter optimization publication-title: Inform. Sci. – reference: S. Gordon, Unsupervised Image Clustering using Probabilistic Continuous Models and Information Theoretic Principles, Tel-Aviv University, Tel-Aviv 69978, Israel, 2006. – volume: 39 start-page: 459 year: 2007 end-page: 471 ident: b0150 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: J. Global Optim. – start-page: 157 year: 1974 end-page: 171 ident: b0020 article-title: Numerical taxonomy with fuzzy sets publication-title: J. Math. Biol. – reference: H. Wedde, M. Farooq, The wisdom of the hive applied to mobile ad-hoc networks, in: Swarm Intelligence Symposium SIS 2005, 2005, pp. 341–348. – volume: 12 start-page: 164 year: 2013 end-page: 173 ident: b0230 article-title: A comparative study of crossover operators for genetic algorithms to solve the job shop scheduling problem publication-title: WSEAS Trans. Comput. – volume: 1 start-page: 224 year: 1979 end-page: 227 ident: b0080 article-title: A cluster separation measure publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – reference: E. Hancer, C. Ozturk, D. Karaboga, Extraction of brain tumors from MRI images with artificial bee colony based segmentation methodology, in: ELECO’2013, Bursa, Turkiye, 2013. – reference: E. Hancer, C. Ozturk, D. Karaboga, Artificial bee colony based image clustering method, in: IEEE Congress on Evolutionary Computation, CEC 2012, Brisbane, Australia, 2012, pp. 1–5. – start-page: 59 year: 2011 end-page: 69 ident: b0300 article-title: Differential artificial bee colony for dynamic environment publication-title: Advances in Computer Science and Information Technology – volume: 2 start-page: 1 year: 2012 end-page: 14 ident: b0245 article-title: Memetic algorithms and memetic computing optimization: a literature review publication-title: Swarm Evol. Comput. – reference: R.H. Turi, Clustering-Based Colour Image Segmentation, Ph.D. Thesis, Monash University, Australia, 2001. – volume: 19 start-page: 279 year: 2009 end-page: 292 ident: b0170 article-title: Neural networks training by artificial bee colony algorithm on pattern classification publication-title: Neural Network World – year: 2014 ident: b0260 article-title: Improved clustering criterion for image clustering with artificial bee colony algorithm publication-title: Pattern Anal. Appl. – reference: J. MacQueen, Some methods for classification and analysis of multivariate observations, in: 5th Berkeley Symp. Math. Stat. Probability, 1967, pp. 281–297. – volume: 13 start-page: 991 year: 2009 end-page: 1005 ident: b0240 article-title: Multiobjective genetic algorithm-based fuzzy clustering of categorical attributes publication-title: IEEE Trans. Evol. Comput. – volume: 55 start-page: 481 year: 2013 end-page: 513 ident: b0180 article-title: A novel differential evolution algorithm for binary optimization publication-title: Comput. Optim. Appl. – reference: J. Puzicha, T. Hofmann, J.M. Buhmann, Histogram Clustering for Unsupervised Image Segmentation, in: CVPR’99, 1999. – volume: 42 start-page: 21 year: 2014 end-page: 57 ident: b0160 article-title: A comprehensive survey: artificial bee colony (ABC) algorithm and applications publication-title: Artif. Intell. Rev. – volume: 8 start-page: 332 year: 2006 end-page: 344 ident: b0255 article-title: Dynamic clustering using particle swarm optimization with application in image segmentation publication-title: Pattern Anal. Appl. – volume: 18 start-page: 1 year: 2013 end-page: 14 ident: b0030 article-title: Utilizing time-linkage property in DOPs: an information sharing based artificial bee colony algorithm for tracking multiple optima in uncertain environments publication-title: Soft Comput. – start-page: 6915 year: 2010 ident: b0140 article-title: Artificial bee colony algorithm publication-title: Scholarpedia – reference: D. Teodorovic, M. Dell’orco, Bee colony optimization – a cooperative learning approach to complex transportation problems, in: 16th mini-EURO Conference on Advanced OR and AI Methods in Transportation, 2005, pp. 51–60. – volume: 3 start-page: 1 year: 1974 end-page: 27 ident: b0040 article-title: A dendrite method for cluster analysis publication-title: Commun. Stat. – year: 2005 ident: b0285 article-title: The bees algorithm publication-title: Manufacturing Engineering Centre – volume: 25 start-page: 485 year: 2014 end-page: 503 ident: b0265 article-title: Color quantization: a short review and an application with artificial bee colony algorithm publication-title: Informatica – volume: 2 start-page: 1462 year: 2007 ident: b0025 article-title: Swarm intelligence publication-title: Scholarpedia – year: 2009 ident: b0060 article-title: Metaheuristic Clustering – volume: 1 start-page: 98 year: 1993 end-page: 110 ident: b0205 article-title: A possibilistic approach to clustering publication-title: IEEE Trans. Fuzzy Syst. – volume: 11 start-page: 6056 year: 2011 end-page: 6065 ident: b0270 article-title: Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm publication-title: Sensors – reference: H. Wedde, M. Farooq, Y. Zhang, BeeHive: An Efficient Fault-Tolerant Routing Algorithm Inspired by Honey Bee Behavior, 2004, pp. 83–94. – reference: L. Anne, X. Descombes, J. Zerubia, Fully unsupervised fuzzy clustering with entropy criterion, in: D. Xavier, Z. Josiane (Eds.), 15th International Conference on Pattern Recognition (ICPR’00), 2000, pp. 3998–3998. – reference: P. Lucic, D. Teodorovic, Bee system: modeling combinatorial optimization transportation engineering problems by swarm intelligence, in: Preprints of the TRISTAN IV Triennial Symposium on Transportation Analysis, Sao Miguel, Azores Islands, Portugal, 2001, pp. 441–445. – volume: 3 start-page: 58 year: 1974 end-page: 72 ident: b0015 article-title: Cluster validity with fuzzy sets publication-title: J. Cybernet. – volume: 11 start-page: 652 year: 2011 end-page: 657 ident: b0175 article-title: A novel clustering approach: artificial bee colony (ABC) algorithm publication-title: Appl. Soft Comput. – start-page: 98 year: 2010 end-page: 105 ident: b0340 article-title: Multiple sequence alignment based on ABC_SA publication-title: Lecture Notes in Computer Science – volume: 8 start-page: 687 year: 2008 end-page: 697 ident: b0155 article-title: On the performance of artificial bee colony (ABC) algorithm publication-title: Appl. Soft Comput. – reference: E. Zitzler, M. Laumanns, Test problems and test data for multiobjective optimizers, in: Systems Optimization, Test Problem Suite, ETH, Zurich, 2014. < – reference: C. Wallace, D. Dowe, Intrinsic classification by MML – the snob program, in: Seventh Australian Joint Conference on Artificial Intelligence, UNE, Armidale, NSW, Australia, 1994, pp. 37–44. – reference: >. – volume: 21 start-page: 2307 year: 2013 end-page: 2328 ident: b0195 article-title: XOR-based artificial bee colony algorithm for binary optimization publication-title: Turk. J. Electr. Eng. Comput. Sci. – reference: G. Pampara, A.P. Engelbrecht, Binary artificial bee colony optimization, in: IEEE Symposium on Swarm Intelligence (SIS), 2011, pp. 1–8. – volume: 3 start-page: 841 year: 1991 end-page: 846 ident: b0335 article-title: Validity measure for fuzzy clustering publication-title: IEEE Trans. Pattern Anal. Mach. Learn. – year: 1995 ident: b0200 article-title: Self-Organizing Maps – volume: 5 start-page: 24 year: 2010 end-page: 31 ident: b0355 article-title: Memetic computation-past, present & future [research frontier] publication-title: IEEE Comput. Intell. Mag. – volume: 4 start-page: 95 year: 1974 end-page: 104 ident: b0095 article-title: Well separated clusters and optimal fuzzy partitions publication-title: J. Cybern. – reference: Z. Yan, Z. Chun-Guang, W. Sheng-Sheng, H. Lan, A dynamic clustering based on genetic algorithm, in: International Conference on Machine Learning and Cybernetics, vol. 221, 2003, pp. 222–224. – reference: M. Dorigo, Optimization Learning and Natural Algorithms, Ph.D. Thesis, Politecnico Di Milano, Italy, 1992. – volume: 11 start-page: 5205 year: 2011 end-page: 5214 ident: b0220 article-title: SAR image segmentation based on artificial bee colony algorithm publication-title: Appl. Soft Comput. – volume: 20 start-page: 661 year: 2006 end-page: 680 ident: b0110 article-title: Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization publication-title: Water Resour. Manage. – volume: 7 start-page: 205 year: 2004 end-page: 220 ident: b0045 article-title: A new cluster validity measure and its application to image compression publication-title: Pattern Anal. Appl. – volume: 26 start-page: 847 year: 2011 end-page: 854 ident: b0050 article-title: An advanced quantum-inspired evolutionary algorithm for unit commitment publication-title: IEEE Trans. Power Syst. – reference: D. Karaboga, An Idea based on Honey Bee Swarm for Numerical Optimization, Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005. – volume: 18 start-page: 1 year: 2013 ident: 10.1016/j.ins.2014.10.060_b0030 article-title: Utilizing time-linkage property in DOPs: an information sharing based artificial bee colony algorithm for tracking multiple optima in uncertain environments publication-title: Soft Comput. – volume: 18 start-page: 847 year: 2012 ident: 10.1016/j.ins.2014.10.060_b0165 article-title: Cluster based wireless sensor network routing using artificial bee colony algorithm publication-title: Wireless Networks doi: 10.1007/s11276-012-0438-z – start-page: 157 year: 1974 ident: 10.1016/j.ins.2014.10.060_b0020 article-title: Numerical taxonomy with fuzzy sets publication-title: J. Math. Biol. – volume: 2 start-page: 1462 year: 2007 ident: 10.1016/j.ins.2014.10.060_b0025 article-title: Swarm intelligence publication-title: Scholarpedia doi: 10.4249/scholarpedia.1462 – volume: 12 start-page: 342 year: 2012 ident: 10.1016/j.ins.2014.10.060_b0185 article-title: DisABC: a new artificial bee colony algorithm for binary optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2011.08.038 – ident: 10.1016/j.ins.2014.10.060_b0035 doi: 10.1109/SIS.2013.6615186 – ident: 10.1016/j.ins.2014.10.060_b0310 – volume: 4 start-page: 95 year: 1974 ident: 10.1016/j.ins.2014.10.060_b0095 article-title: Well separated clusters and optimal fuzzy partitions publication-title: J. Cybern. doi: 10.1080/01969727408546059 – ident: 10.1016/j.ins.2014.10.060_b0215 – start-page: 98 year: 2010 ident: 10.1016/j.ins.2014.10.060_b0340 article-title: Multiple sequence alignment based on ABC_SA doi: 10.1007/978-3-642-16527-6_14 – volume: 12 start-page: 164 year: 2013 ident: 10.1016/j.ins.2014.10.060_b0230 article-title: A comparative study of crossover operators for genetic algorithms to solve the job shop scheduling problem publication-title: WSEAS Trans. Comput. – volume: 1 start-page: 224 year: 1979 ident: 10.1016/j.ins.2014.10.060_b0080 article-title: A cluster separation measure publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.1979.4766909 – start-page: 6915 year: 2010 ident: 10.1016/j.ins.2014.10.060_b0140 article-title: Artificial bee colony algorithm publication-title: Scholarpedia doi: 10.4249/scholarpedia.6915 – volume: 3 start-page: 1 year: 1974 ident: 10.1016/j.ins.2014.10.060_b0040 article-title: A dendrite method for cluster analysis publication-title: Commun. Stat. – volume: 3 start-page: 841 year: 1991 ident: 10.1016/j.ins.2014.10.060_b0335 article-title: Validity measure for fuzzy clustering publication-title: IEEE Trans. Pattern Anal. Mach. Learn. doi: 10.1109/34.85677 – volume: 9 start-page: 226 year: 2009 ident: 10.1016/j.ins.2014.10.060_b0075 article-title: Automatic image pixel clustering with an improved differential evolution publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2007.12.008 – ident: 10.1016/j.ins.2014.10.060_b0280 doi: 10.1109/SIS.2011.5952562 – ident: 10.1016/j.ins.2014.10.060_b0305 – ident: 10.1016/j.ins.2014.10.060_b0135 – start-page: 51 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0330 article-title: Improved artificial bee colony algorithm with chaos – volume: 21 start-page: 2307 year: 2013 ident: 10.1016/j.ins.2014.10.060_b0195 article-title: XOR-based artificial bee colony algorithm for binary optimization publication-title: Turk. J. Electr. Eng. Comput. Sci. doi: 10.3906/elk-1203-104 – volume: 1 start-page: 98 year: 1993 ident: 10.1016/j.ins.2014.10.060_b0205 article-title: A possibilistic approach to clustering publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/91.227387 – volume: 192 start-page: 120 year: 2012 ident: 10.1016/j.ins.2014.10.060_b0005 article-title: A modified artificial bee colony algorithm for real-parameter optimization publication-title: Inform. Sci. doi: 10.1016/j.ins.2010.07.015 – year: 2005 ident: 10.1016/j.ins.2014.10.060_b0285 article-title: The bees algorithm – ident: 10.1016/j.ins.2014.10.060_b0275 – volume: 55 start-page: 481 year: 2013 ident: 10.1016/j.ins.2014.10.060_b0180 article-title: A novel differential evolution algorithm for binary optimization publication-title: Comput. Optim. Appl. doi: 10.1007/s10589-012-9521-8 – ident: 10.1016/j.ins.2014.10.060_b0250 – year: 2010 ident: 10.1016/j.ins.2014.10.060_b0360 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. doi: 10.1016/j.amc.2010.08.049 – ident: 10.1016/j.ins.2014.10.060_b0090 – ident: 10.1016/j.ins.2014.10.060_b0315 – volume: 195 start-page: 124 year: 2012 ident: 10.1016/j.ins.2014.10.060_b0210 article-title: Integration of particle swarm optimization and genetic algorithm for dynamic clustering publication-title: Inform. Sci. doi: 10.1016/j.ins.2012.01.021 – volume: 3 start-page: 58 year: 1974 ident: 10.1016/j.ins.2014.10.060_b0015 article-title: Cluster validity with fuzzy sets publication-title: J. Cybernet. doi: 10.1080/01969727308546047 – volume: 39 start-page: 459 year: 2007 ident: 10.1016/j.ins.2014.10.060_b0150 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: J. Global Optim. doi: 10.1007/s10898-007-9149-x – ident: 10.1016/j.ins.2014.10.060_b0125 doi: 10.1109/ELECO.2013.6713896 – volume: 44 start-page: 1884 year: 2014 ident: 10.1016/j.ins.2014.10.060_b0070 article-title: A spatially informative optic flow model of bee colony with saccadic flight strategy for global optimization publication-title: IEEE Trans. Cybernet. doi: 10.1109/TCYB.2014.2298916 – start-page: 59 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0300 article-title: Differential artificial bee colony for dynamic environment – volume: 8 start-page: 332 year: 2006 ident: 10.1016/j.ins.2014.10.060_b0255 article-title: Dynamic clustering using particle swarm optimization with application in image segmentation publication-title: Pattern Anal. Appl. doi: 10.1007/s10044-005-0015-5 – ident: 10.1016/j.ins.2014.10.060_b0320 doi: 10.1109/SIS.2005.1501641 – volume: 11 start-page: 6056 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0270 article-title: Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm publication-title: Sensors doi: 10.3390/s110606056 – ident: 10.1016/j.ins.2014.10.060_b0010 – ident: 10.1016/j.ins.2014.10.060_b0325 doi: 10.1007/978-3-540-28646-2_8 – volume: 26 start-page: 847 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0050 article-title: An advanced quantum-inspired evolutionary algorithm for unit commitment publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2010.2059716 – volume: 13 start-page: 991 year: 2009 ident: 10.1016/j.ins.2014.10.060_b0240 article-title: Multiobjective genetic algorithm-based fuzzy clustering of categorical attributes publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2009.2012163 – year: 1976 ident: 10.1016/j.ins.2014.10.060_b0085 – year: 1994 ident: 10.1016/j.ins.2014.10.060_b0235 – ident: 10.1016/j.ins.2014.10.060_b0295 doi: 10.1016/S0167-8655(99)00056-2 – ident: 10.1016/j.ins.2014.10.060_b0100 doi: 10.1109/MHS.1995.494215 – year: 2004 ident: 10.1016/j.ins.2014.10.060_b0190 – year: 2014 ident: 10.1016/j.ins.2014.10.060_b0260 article-title: Improved clustering criterion for image clustering with artificial bee colony algorithm publication-title: Pattern Anal. Appl. doi: 10.1007/s10044-014-0365-y – volume: 25 start-page: 485 year: 2014 ident: 10.1016/j.ins.2014.10.060_b0265 article-title: Color quantization: a short review and an application with artificial bee colony algorithm publication-title: Informatica doi: 10.15388/Informatica.2014.25 – volume: 84 start-page: 285 year: 2001 ident: 10.1016/j.ins.2014.10.060_b0290 article-title: Spatial models for fuzzy clustering publication-title: Comput. Vis. Image Underst. doi: 10.1006/cviu.2001.0951 – volume: 7 start-page: 205 year: 2004 ident: 10.1016/j.ins.2014.10.060_b0045 article-title: A new cluster validity measure and its application to image compression publication-title: Pattern Anal. Appl. doi: 10.1007/s10044-004-0218-1 – year: 1995 ident: 10.1016/j.ins.2014.10.060_b0200 – ident: 10.1016/j.ins.2014.10.060_b0345 – volume: 19 start-page: 279 year: 2009 ident: 10.1016/j.ins.2014.10.060_b0170 article-title: Neural networks training by artificial bee colony algorithm on pattern classification publication-title: Neural Network World – volume: 13 start-page: 4676 year: 2013 ident: 10.1016/j.ins.2014.10.060_b0065 article-title: Synergizing fitness learning with proximity-based food source selection in artificial bee colony algorithm for numerical optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2013.07.009 – volume: 31 start-page: 61 year: 2009 ident: 10.1016/j.ins.2014.10.060_b0145 article-title: A survey: algorithms simulating bee swarm intelligence publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-009-9127-4 – volume: 38 start-page: 218 year: 2008 ident: 10.1016/j.ins.2014.10.060_b0055 article-title: Automatic clustering using an improved differential evolution algorithm publication-title: IEEE Trans. Syst., Man Cybernet., Part A: Syst. Hum. doi: 10.1109/TSMCA.2007.909595 – ident: 10.1016/j.ins.2014.10.060_b0115 doi: 10.1109/ICDM.2001.989517 – volume: 11 start-page: 5205 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0220 article-title: SAR image segmentation based on artificial bee colony algorithm publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2011.05.039 – ident: 10.1016/j.ins.2014.10.060_b0225 – ident: 10.1016/j.ins.2014.10.060_b0365 – volume: 31 start-page: 264 year: 1999 ident: 10.1016/j.ins.2014.10.060_b0130 article-title: Data clustering: a review publication-title: ACM Comput. Surv. doi: 10.1145/331499.331504 – volume: 11 start-page: 652 year: 2011 ident: 10.1016/j.ins.2014.10.060_b0175 article-title: A novel clustering approach: artificial bee colony (ABC) algorithm publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2009.12.025 – volume: 42 start-page: 21 year: 2014 ident: 10.1016/j.ins.2014.10.060_b0160 article-title: A comprehensive survey: artificial bee colony (ABC) algorithm and applications publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-012-9328-0 – year: 2009 ident: 10.1016/j.ins.2014.10.060_b0060 – volume: 20 start-page: 661 year: 2006 ident: 10.1016/j.ins.2014.10.060_b0110 article-title: Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization publication-title: Water Resour. Manage. doi: 10.1007/s11269-005-9001-3 – volume: 2 start-page: 1 year: 2012 ident: 10.1016/j.ins.2014.10.060_b0245 article-title: Memetic algorithms and memetic computing optimization: a literature review publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.11.003 – year: 2005 ident: 10.1016/j.ins.2014.10.060_b0350 article-title: Engineering optimizations via nature-inspired virtual bee algorithms – ident: 10.1016/j.ins.2014.10.060_b0105 – volume: 5 start-page: 24 year: 2010 ident: 10.1016/j.ins.2014.10.060_b0355 article-title: Memetic computation-past, present & future [research frontier] publication-title: IEEE Comput. Intell. Mag. doi: 10.1109/MCI.2010.936309 – volume: 8 start-page: 687 year: 2008 ident: 10.1016/j.ins.2014.10.060_b0155 article-title: On the performance of artificial bee colony (ABC) algorithm publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2007.05.007 – ident: 10.1016/j.ins.2014.10.060_b0120 doi: 10.1109/CEC.2012.6252919 |
| SSID | ssj0004766 |
| Score | 2.5150552 |
| Snippet | This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 154 |
| SubjectTerms | Algorithms Artificial bee colony Binary optimization Children Dynamic clustering Foods Genetic algorithm Genetics Knapsack problem Mathematical models Operators Optimization Swarm intelligence |
| Title | A novel binary artificial bee colony algorithm based on genetic operators |
| URI | https://dx.doi.org/10.1016/j.ins.2014.10.060 https://www.proquest.com/docview/1660079925 |
| Volume | 297 |
| WOSCitedRecordID | wos000347862200008&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 0020-0255 databaseCode: AIEXJ dateStart: 19950101 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0004766 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3Nb9MwFLeg4wAHBAPEgCEjIQ5EQXEcx_axGkMM0OAwpN4ix7HHpiyp2m6a-Ot5jp00K9rEDlyiJHKe0r5f3offF0JvOVdgtQsbU1byOOPaxKAE81hoQpnOrTZ-ask3fngoZjP5I1RcL7txArxpxOWlnP9XVsM9YLYrnb0FuweicAPOgelwBLbD8Z8YP42a9sLUUekrbd2K0CWiNC41vQZ_P1L1cbs4Wf06i5waq1zIAAi6gsaonZsu9L4c262haqkDS1CagzH-_TeorU6o7pla1WuZBot8Mc3ZaNf5q1oA7vx27kcnqK5sPBAWd1lsY2EKnqdzScbCNPXZtkEcEt8gOmhW4keE_CW0_f7BKXgarn86yT64dDs_ZeBqg-wNxTWkE_aZaqcFkCgcCbgugMRdtJVyJsUEbU0P9mdf1hWz3Eex-5_Qx7u7zL-N97jOYtnQ3Z1BcvQIPQyeBJ56BDxGd0yzjR6M-ktuo91QlYLf4REDcZDnT9DBFHdYwR4reI0VDFjBHit4wArusIKBQsAKHrDyFP38tH-09zkOszViTWmyiqVKhGY2KbMqz7Wx2pIKbHsllOvhSCtpGTfU2pwIrVTJONUp15IaKi3RSUmfoUnTNuY5wpxSWiWmLKkRmcpSBUZuZmzCXAzbErGDkv7_K3RoPO_mn9TFtXzbQe-HR-a-68pNi7OeKUX4Arw5WADAbnrsTc_AAkSqi5OpxrTny4LkbmiDlCl7cZv3eInurz-TV2iyWpybXXRPX6xOlovXAYF_AJ2xmY4 |
| linkProvider | Elsevier |
| 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+novel+binary+artificial+bee+colony+algorithm+based+on+genetic+operators&rft.jtitle=Information+sciences&rft.au=Ozturk%2C+Celal&rft.au=Hancer%2C+Emrah&rft.au=Karaboga%2C+Dervis&rft.date=2015-03-10&rft.issn=0020-0255&rft.volume=297&rft.spage=154&rft.epage=170&rft_id=info:doi/10.1016%2Fj.ins.2014.10.060&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_ins_2014_10_060 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0020-0255&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0020-0255&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0020-0255&client=summon |