Binary artificial algae algorithm for multidimensional knapsack problems
[Display omitted] •A novel binary artificial algae algorithm is proposed for solving MKPs.•The method is composed of discrete process, repair operators and elite local search.•The results show the proposed method outperforms many existing algorithms. The multidimensional knapsack problem (MKP) is a...
Saved in:
| Published in | Applied soft computing Vol. 43; pp. 583 - 595 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.06.2016
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1568-4946 1872-9681 |
| DOI | 10.1016/j.asoc.2016.02.027 |
Cover
| Abstract | [Display omitted]
•A novel binary artificial algae algorithm is proposed for solving MKPs.•The method is composed of discrete process, repair operators and elite local search.•The results show the proposed method outperforms many existing algorithms.
The multidimensional knapsack problem (MKP) is a well-known NP-hard optimization problem. Various meta-heuristic methods are dedicated to solve this problem in literature. Recently a new meta-heuristic algorithm, called artificial algae algorithm (AAA), was presented, which has been successfully applied to solve various continuous optimization problems. However, due to its continuous nature, AAA cannot settle the discrete problem straightforwardly such as MKP. In view of this, this paper proposes a binary artificial algae algorithm (BAAA) to efficiently solve MKP. This algorithm is composed of discrete process, repair operators and elite local search. In discrete process, two logistic functions with different coefficients of curve are studied to achieve good discrete process results. Repair operators are performed to make the solution feasible and increase the efficiency. Finally, elite local search is introduced to improve the quality of solutions. To demonstrate the efficiency of our proposed algorithm, simulations and evaluations are carried out with total of 94 benchmark problems and compared with other bio-inspired state-of-the-art algorithms in the recent years including MBPSO, BPSOTVAC, CBPSOTVAC, GADS, bAFSA, and IbAFSA. The results show the superiority of BAAA to many compared existing algorithms. |
|---|---|
| AbstractList | [Display omitted]
•A novel binary artificial algae algorithm is proposed for solving MKPs.•The method is composed of discrete process, repair operators and elite local search.•The results show the proposed method outperforms many existing algorithms.
The multidimensional knapsack problem (MKP) is a well-known NP-hard optimization problem. Various meta-heuristic methods are dedicated to solve this problem in literature. Recently a new meta-heuristic algorithm, called artificial algae algorithm (AAA), was presented, which has been successfully applied to solve various continuous optimization problems. However, due to its continuous nature, AAA cannot settle the discrete problem straightforwardly such as MKP. In view of this, this paper proposes a binary artificial algae algorithm (BAAA) to efficiently solve MKP. This algorithm is composed of discrete process, repair operators and elite local search. In discrete process, two logistic functions with different coefficients of curve are studied to achieve good discrete process results. Repair operators are performed to make the solution feasible and increase the efficiency. Finally, elite local search is introduced to improve the quality of solutions. To demonstrate the efficiency of our proposed algorithm, simulations and evaluations are carried out with total of 94 benchmark problems and compared with other bio-inspired state-of-the-art algorithms in the recent years including MBPSO, BPSOTVAC, CBPSOTVAC, GADS, bAFSA, and IbAFSA. The results show the superiority of BAAA to many compared existing algorithms. |
| Author | Jung, Kwang-Hyo Wang, Xiangyu Wu, Changzhi Yang, Zhijing Lee, Jae-Myung Zhang, Xuedong Li, Jing |
| Author_xml | – sequence: 1 givenname: Xuedong surname: Zhang fullname: Zhang, Xuedong organization: School of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233000, China – sequence: 2 givenname: Changzhi surname: Wu fullname: Wu, Changzhi organization: Australasian Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Perth, WA 6845, Australia – sequence: 3 givenname: Jing surname: Li fullname: Li, Jing organization: Information and Intelligence Engineering Department, Anhui Vocational College of Electronics & Information Technology, Bengbu 233000, China – sequence: 4 givenname: Xiangyu surname: Wang fullname: Wang, Xiangyu organization: Australasian Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Perth, WA 6845, Australia – sequence: 5 givenname: Zhijing surname: Yang fullname: Yang, Zhijing email: yzhj@gdut.edu.cn organization: School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China – sequence: 6 givenname: Jae-Myung surname: Lee fullname: Lee, Jae-Myung organization: Department of Naval Architecture and Ocean Engineering, Pusan National University, Busan, South Korea – sequence: 7 givenname: Kwang-Hyo surname: Jung fullname: Jung, Kwang-Hyo organization: Department of Naval Architecture and Ocean Engineering, Pusan National University, Busan, South Korea |
| BookMark | eNp9kMFOwzAMhiM0JLbBC3DqC7QkaZc2EheYYEOaxAXOUZo64K1tpiQg8fakGicOkyz7P_iz9f8LMhvdCITcMlowysTdvtDBmYInXVCeqr4gc9bUPJeiYbOkV6LJK1mJK7IIYU_TouTNnGwfcdT-J9M-okWDus90_6Fh6s5j_Bwy63w2fPUROxxgDOjGtHQY9TFoc8iO3rU9DOGaXFrdB7j5m0vy_vz0tt7mu9fNy_phl5uS0pgDFZUQjUjfBeO6rm3ZtRYMtFXXtQAaypYmqbta2ko0diVqkFIKYUxrmCyXhJ_uGu9C8GDV0eOQLChG1ZSF2qspCzVloShPVSeo-QcZjDomK9Fr7M-j9ycUkqlvBK-CQRgNdOjBRNU5PIf_Akpofvs |
| CitedBy_id | crossref_primary_10_1016_j_apm_2017_05_001 crossref_primary_10_1007_s00500_017_2744_y crossref_primary_10_1109_ACCESS_2021_3124710 crossref_primary_10_1016_j_cie_2021_107469 crossref_primary_10_1016_j_envres_2021_112574 crossref_primary_10_1016_j_jestch_2020_07_001 crossref_primary_10_1080_0952813X_2020_1785020 crossref_primary_10_1016_j_apm_2017_06_010 crossref_primary_10_1007_s13042_020_01085_8 crossref_primary_10_3390_a15100366 crossref_primary_10_1155_2018_3010514 crossref_primary_10_1016_j_asoc_2020_107077 crossref_primary_10_1016_j_advengsoft_2021_102998 crossref_primary_10_1016_j_asoc_2022_108443 crossref_primary_10_1016_j_bspc_2023_105073 crossref_primary_10_1155_2018_8395193 crossref_primary_10_1016_j_cie_2019_04_025 crossref_primary_10_1155_2017_8404231 crossref_primary_10_17341_gazimmfd_1111302 crossref_primary_10_1016_j_apm_2017_09_015 crossref_primary_10_1016_j_eswa_2020_113298 crossref_primary_10_55195_jscai_1560068 crossref_primary_10_1186_s40537_024_00931_8 crossref_primary_10_1016_j_fcij_2018_06_001 crossref_primary_10_1007_s10489_017_0972_6 crossref_primary_10_1007_s00521_023_09190_9 crossref_primary_10_1016_j_asoc_2022_108630 crossref_primary_10_1016_j_swevo_2021_100993 crossref_primary_10_1016_j_iswa_2025_200502 crossref_primary_10_1155_2018_8705134 crossref_primary_10_4236_ajor_2018_85023 crossref_primary_10_1016_j_asoc_2017_02_009 crossref_primary_10_1016_j_cie_2019_06_027 crossref_primary_10_1109_ACCESS_2022_3156593 crossref_primary_10_1016_j_asoc_2019_105576 crossref_primary_10_1007_s00521_022_07932_9 crossref_primary_10_1186_s40537_024_01055_9 crossref_primary_10_3390_math8040507 crossref_primary_10_1007_s11063_023_11171_x crossref_primary_10_1109_TCYB_2020_3002495 crossref_primary_10_1016_j_asoc_2016_05_021 crossref_primary_10_1016_j_asoc_2020_107054 crossref_primary_10_1016_j_asoc_2019_105611 crossref_primary_10_1016_j_asoc_2018_01_001 crossref_primary_10_1007_s13369_024_09222_z crossref_primary_10_1007_s40747_021_00410_0 crossref_primary_10_1016_j_swevo_2017_04_004 crossref_primary_10_1016_j_eswa_2020_114288 crossref_primary_10_1007_s13042_022_01518_6 crossref_primary_10_1007_s00521_022_07058_y crossref_primary_10_1007_s13369_021_05677_6 crossref_primary_10_1016_j_eswa_2021_115078 crossref_primary_10_1007_s00366_019_00853_7 crossref_primary_10_1007_s13369_021_05415_y crossref_primary_10_1016_j_swevo_2018_08_006 crossref_primary_10_1080_0305215X_2019_1657113 crossref_primary_10_1016_j_jestch_2024_101684 crossref_primary_10_1007_s13042_017_0772_7 crossref_primary_10_1016_j_asoc_2021_107346 crossref_primary_10_3390_electronics12092042 crossref_primary_10_3934_jimo_2017021 |
| Cites_doi | 10.1109/TSP.2014.2371779 10.1023/A:1009642405419 10.1016/j.swevo.2013.09.002 10.1016/S0377-2217(02)00149-2 10.1016/j.asoc.2014.10.030 10.1016/j.ejor.2006.02.058 10.1109/TSP.2014.2312326 10.1016/j.eswa.2013.11.040 10.1016/j.sigpro.2013.11.018 10.1016/S0377-2217(03)00274-1 10.1287/opre.1080.0529 10.1016/j.asoc.2015.01.022 10.1287/mnsc.48.4.550.208 10.1016/j.cor.2015.04.018 10.1016/j.amc.2012.05.001 10.1016/j.asoc.2015.03.003 10.1287/ijoc.1090.0344 10.1016/S0377-2217(97)00296-8 10.1016/j.apm.2013.08.009 10.1109/TSP.2011.2171956 10.1002/1520-6750(198704)34:2<161::AID-NAV3220340203>3.0.CO;2-A 10.1016/j.cor.2011.10.016 10.1016/j.asoc.2010.07.019 10.1016/j.ins.2012.12.043 |
| ContentType | Journal Article |
| Copyright | 2016 Elsevier B.V. |
| Copyright_xml | – notice: 2016 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.asoc.2016.02.027 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1872-9681 |
| EndPage | 595 |
| ExternalDocumentID | 10_1016_j_asoc_2016_02_027 S1568494616300783 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1~. 1~5 23M 4.4 457 4G. 53G 5GY 5VS 6J9 7-5 71M 8P~ AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABFNM ABFRF ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFO ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD ADTZH AEBSH AECPX AEFWE AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HVGLF HZ~ IHE J1W JJJVA KOM M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SDF SDG SES SEW SPC SPCBC SST SSV SSZ T5K UHS UNMZH ~G- AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c300t-e0646686692612a77f3dbfeceb4ddbeeae3b04ddad79f468f567e99966ccbc193 |
| IEDL.DBID | .~1 |
| ISSN | 1568-4946 |
| IngestDate | Wed Oct 01 02:32:06 EDT 2025 Thu Apr 24 22:59:39 EDT 2025 Fri Feb 23 02:24:52 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Artificial algae algorithm Pseudo-utility ratio Multidimensional knapsack problem Elite local search |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c300t-e0646686692612a77f3dbfeceb4ddbeeae3b04ddad79f468f567e99966ccbc193 |
| PageCount | 13 |
| ParticipantIDs | crossref_primary_10_1016_j_asoc_2016_02_027 crossref_citationtrail_10_1016_j_asoc_2016_02_027 elsevier_sciencedirect_doi_10_1016_j_asoc_2016_02_027 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | June 2016 2016-06-00 |
| PublicationDateYYYYMMDD | 2016-06-01 |
| PublicationDate_xml | – month: 06 year: 2016 text: June 2016 |
| PublicationDecade | 2010 |
| PublicationTitle | Applied soft computing |
| PublicationYear | 2016 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Fréville (bib0030) 2004; 155 Li, Liang, Chang (bib0055) 2012; 39 Ling, Ho, Subramaniam, Georgakis, Cao, Dai (bib0025) 2014; 98 Chih (bib0150) 2015; 26 Suganthan, Hansen, Liang, Deb, Chen, Auger, Tiwari (bib0170) 2005 Baykasoğlu, Ozsoydan (bib0105) 2014; 41 Kong, Gao, Ouyang, Li (bib0110) 2015; 63 Uymaz, Tezel, Yel (bib0165) 2015; 31 Azad, Rocha, Fernandes (bib0125) 2012 Hembecker, Lopes, Godoy (bib0095) 2007 Zhang, Pan, Zhang, Duan (bib0115) 2015; 29 Chih, Lin, Chern, Ou (bib0145) 2014; 38 Hanafi, Freville (bib0085) 1998; 106 Pirkul (bib0175) 1987; 34 Varnamkhasti (bib0045) 2012; 4 Subramaniam, Ling, Georgakis (bib0020) 2012; 60 Sakawa, Kato (bib0080) 2003; 144 Chu, Beasley (bib0070) 1998; 4 Kennedy, Eberhart (bib0140) 1997 Zou, Gao, Li, Wu (bib0160) 2011; 11 Binitha, Sathya (bib0135) 2012; 2 Balev, Yanev, Fréville, Andonov (bib0050) 2008; 186 Yang, Cui, Xiao, Gandomi, Karamanoglu (bib0130) 2013 Gallardo, Cotta, Fernández (bib0065) 2005 Vasquez, Hao (bib0060) 2001 Ling, Ho, Cao, Dai (bib0005) 2013; 9 Ling, Tian, Ho, Siu, Teo, Dai (bib0010) 2015; 63 Song, Schmeiser (bib0185) 2009; 57 Azad, Rocha, Fernandes (bib0120) 2014; 14 Djannaty, Doostdar (bib0075) 2008; 3 Bansal, Deep (bib0100) 2012; 218 Ling, Ho, Teo, Siu, Cao, Dai (bib0015) 2014; 62 Bertsimas, Demir (bib0035) 2002; 48 Xiangyong Konga, Gaoa (bib0180) 2015; 63 Qian, Ding (bib0090) 2007; 16 Wang, Yang, Xu, Niu, Pardalos, Fei (bib0155) 2013; 232 Puchinger, Raidl, Pferschy (bib0040) 2010; 22 Chu (10.1016/j.asoc.2016.02.027_bib0070) 1998; 4 Qian (10.1016/j.asoc.2016.02.027_bib0090) 2007; 16 Ling (10.1016/j.asoc.2016.02.027_bib0010) 2015; 63 Chih (10.1016/j.asoc.2016.02.027_bib0150) 2015; 26 Azad (10.1016/j.asoc.2016.02.027_bib0125) 2012 Fréville (10.1016/j.asoc.2016.02.027_bib0030) 2004; 155 Hanafi (10.1016/j.asoc.2016.02.027_bib0085) 1998; 106 Xiangyong Konga (10.1016/j.asoc.2016.02.027_bib0180) 2015; 63 Chih (10.1016/j.asoc.2016.02.027_bib0145) 2014; 38 Ling (10.1016/j.asoc.2016.02.027_bib0005) 2013; 9 Kennedy (10.1016/j.asoc.2016.02.027_bib0140) 1997 Djannaty (10.1016/j.asoc.2016.02.027_bib0075) 2008; 3 Ling (10.1016/j.asoc.2016.02.027_bib0025) 2014; 98 Puchinger (10.1016/j.asoc.2016.02.027_bib0040) 2010; 22 Bansal (10.1016/j.asoc.2016.02.027_bib0100) 2012; 218 Sakawa (10.1016/j.asoc.2016.02.027_bib0080) 2003; 144 Hembecker (10.1016/j.asoc.2016.02.027_bib0095) 2007 Zhang (10.1016/j.asoc.2016.02.027_bib0115) 2015; 29 Azad (10.1016/j.asoc.2016.02.027_bib0120) 2014; 14 Gallardo (10.1016/j.asoc.2016.02.027_bib0065) 2005 Baykasoğlu (10.1016/j.asoc.2016.02.027_bib0105) 2014; 41 Subramaniam (10.1016/j.asoc.2016.02.027_bib0020) 2012; 60 Pirkul (10.1016/j.asoc.2016.02.027_bib0175) 1987; 34 Ling (10.1016/j.asoc.2016.02.027_bib0015) 2014; 62 Yang (10.1016/j.asoc.2016.02.027_bib0130) 2013 Wang (10.1016/j.asoc.2016.02.027_bib0155) 2013; 232 Balev (10.1016/j.asoc.2016.02.027_bib0050) 2008; 186 Uymaz (10.1016/j.asoc.2016.02.027_bib0165) 2015; 31 Song (10.1016/j.asoc.2016.02.027_bib0185) 2009; 57 Binitha (10.1016/j.asoc.2016.02.027_bib0135) 2012; 2 Zou (10.1016/j.asoc.2016.02.027_bib0160) 2011; 11 Suganthan (10.1016/j.asoc.2016.02.027_bib0170) 2005 Varnamkhasti (10.1016/j.asoc.2016.02.027_bib0045) 2012; 4 Li (10.1016/j.asoc.2016.02.027_bib0055) 2012; 39 Kong (10.1016/j.asoc.2016.02.027_bib0110) 2015; 63 Bertsimas (10.1016/j.asoc.2016.02.027_bib0035) 2002; 48 Vasquez (10.1016/j.asoc.2016.02.027_bib0060) 2001 |
| References_xml | – volume: 41 start-page: 3712 year: 2014 end-page: 3725 ident: bib0105 article-title: An improved firefly algorithm for solving dynamic multidimensional knapsack problems publication-title: Expert Syst. Appl. – volume: 63 start-page: 7 year: 2015 end-page: 22 ident: bib0180 article-title: Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm publication-title: Comput. Oper. Res. – volume: 2 start-page: 137 year: 2012 end-page: 151 ident: bib0135 article-title: A survey of bio inspired optimization algorithms publication-title: Int. J. Soft Comput. Eng. – volume: 106 start-page: 659 year: 1998 end-page: 675 ident: bib0085 article-title: An efficient tabu search approach for the 0–1 multidimensional knapsack problem publication-title: Eur. J. Oper. Res. – start-page: 72 year: 2012 end-page: 86 ident: bib0125 article-title: Solving multidimensional 0–1 knapsack problem with an artificial fish swarm algorithm publication-title: Computational Science and Its Applications-ICCSA 2012 – volume: 9 start-page: 588 year: 2013 end-page: 593 ident: bib0005 article-title: Efficient complex-valued finite word length allpass rational IIR PCLS filter design via functional inequality constrained integer programming with bit plane searching technique publication-title: Mediterr. J. Electron. Commun. – volume: 98 start-page: 1 year: 2014 end-page: 22 ident: bib0025 article-title: Optimal design of Hermitian transform and vectors of both mask and window coefficients for denoising applications with both unknown noise characteristics and distortions publication-title: Signal Process. – year: 2013 ident: bib0130 article-title: Swarm Intelligence and Bio-inspired Computation: Theory and Applications, Newnes – volume: 218 start-page: 11042 year: 2012 end-page: 11061 ident: bib0100 article-title: A modified binary particle swarm optimization for knapsack problems publication-title: Appl. Math. Comput. – volume: 38 start-page: 1338 year: 2014 end-page: 1350 ident: bib0145 article-title: Particle swarm optimization with time-varying acceleration coefficients for the multidimensional knapsack problem publication-title: Appl. Math. Model. – volume: 34 start-page: 161 year: 1987 end-page: 172 ident: bib0175 article-title: A heuristic solution procedure for the multiconstraint zero-one knapsack problem publication-title: Nav. Res. Logist. – volume: 11 start-page: 1556 year: 2011 end-page: 1564 ident: bib0160 article-title: Solving 0–1 knapsack problem by a novel global harmony search algorithm publication-title: Appl. Soft Comput. – volume: 62 start-page: 2517 year: 2014 end-page: 2530 ident: bib0015 article-title: Optimal design of cosine modulated nonuniform linear phase FIR filter bank via both stretching and shifting frequency response of single prototype filter publication-title: IEEE Trans. Signal Process. – volume: 4 start-page: 37 year: 2012 end-page: 47 ident: bib0045 article-title: Overview of the algorithms for solving the multidimensional knapsack problems publication-title: Adv. Stud. Biol. – volume: 144 start-page: 581 year: 2003 end-page: 597 ident: bib0080 article-title: Genetic algorithms with double strings for 0–1 programming problems publication-title: Eur. J. Oper. Res. – volume: 57 start-page: 109 year: 2009 end-page: 117 ident: bib0185 article-title: Omitting meaningless digits in point estimates: the probability guarantee of leading-digit rules publication-title: Oper. Res. – start-page: 4104 year: 1997 end-page: 4108 ident: bib0140 article-title: A discrete binary version of the particle swarm algorithm publication-title: 1997 IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, vol. 5 – volume: 60 start-page: 489 year: 2012 end-page: 493 ident: bib0020 article-title: Filtering in rotated time-frequency domains with unknown noise statistics publication-title: IEEE Trans. Signal Process. – volume: 63 start-page: 466 year: 2015 end-page: 481 ident: bib0010 article-title: Maximally decimated paraunitary linear phase FIR filter bank design via iterative SVD approach publication-title: IEEE Trans. Signal Process. – volume: 16 start-page: 320 year: 2007 ident: bib0090 article-title: Simulated annealing for the 0/1 multidimensional knapsack problem publication-title: Numer. Math. Engl. Ser. – volume: 232 start-page: 58 year: 2013 end-page: 87 ident: bib0155 article-title: An improved adaptive binary harmony search algorithm publication-title: Inf. Sci. – start-page: 328 year: 2001 end-page: 333 ident: bib0060 article-title: A hybrid approach for the 0–1 multidimensional knapsack problem publication-title: IJCAI – volume: 186 start-page: 63 year: 2008 end-page: 76 ident: bib0050 article-title: A dynamic programming based reduction procedure for the multidimensional 0–1 knapsack problem publication-title: Eur. J. Oper. Res. – volume: 29 start-page: 288 year: 2015 end-page: 297 ident: bib0115 article-title: An effective hybrid harmony search-based algorithm for solving multidimensional knapsack problems publication-title: Appl. Soft Comput. – start-page: 358 year: 2007 end-page: 365 ident: bib0095 article-title: Particle swarm optimization for the multidimensional knapsack problem publication-title: Adaptive and Natural Computing Algorithms – volume: 14 start-page: 66 year: 2014 end-page: 75 ident: bib0120 article-title: Improved binary artificial fish swarm algorithm for the 0–1 multidimensional knapsack problems publication-title: Swarm Evol. Comput. – year: 2005 ident: bib0170 article-title: Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization, KanGAL report 2005005 – volume: 39 start-page: 2111 year: 2012 end-page: 2121 ident: bib0055 article-title: Solving the multidimensional knapsack problems with generalized upper bound constraints by the adaptive memory projection method publication-title: Comput. Oper. Res. – volume: 4 start-page: 63 year: 1998 end-page: 86 ident: bib0070 article-title: A genetic algorithm for the multidimensional knapsack problem publication-title: J. Heuristics – volume: 48 start-page: 550 year: 2002 end-page: 565 ident: bib0035 article-title: An approximate dynamic programming approach to multidimensional knapsack problems publication-title: Manag. Sci. – volume: 26 start-page: 378 year: 2015 end-page: 389 ident: bib0150 article-title: Self-adaptive check and repair operator-based particle swarm optimization for the multidimensional knapsack problem publication-title: Appl. Soft Comput. – volume: 3 start-page: 443 year: 2008 end-page: 456 ident: bib0075 article-title: A hybrid genetic algorithm for the multidimensional knapsack problem publication-title: Int. J. Contemp. Math. Sci. – volume: 31 start-page: 153 year: 2015 end-page: 171 ident: bib0165 article-title: Artificial algae algorithm (AAA) for nonlinear global optimization publication-title: Appl. Soft Comput. – start-page: 21 year: 2005 end-page: 30 ident: bib0065 article-title: Solving the multidimensional knapsack problem using an evolutionary algorithm hybridized with branch and bound publication-title: Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach – volume: 155 start-page: 1 year: 2004 end-page: 21 ident: bib0030 article-title: The multidimensional 0–1 knapsack problem: an overview publication-title: Eur. J. Oper. Res. – volume: 22 start-page: 250 year: 2010 end-page: 265 ident: bib0040 article-title: The multidimensional knapsack problem: structure and algorithms publication-title: INFORMS J. Comput. – volume: 63 start-page: 7 year: 2015 end-page: 22 ident: bib0110 article-title: Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm publication-title: Comput. Oper. Res. – volume: 63 start-page: 466 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0010 article-title: Maximally decimated paraunitary linear phase FIR filter bank design via iterative SVD approach publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2014.2371779 – start-page: 72 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0125 article-title: Solving multidimensional 0–1 knapsack problem with an artificial fish swarm algorithm – volume: 4 start-page: 63 year: 1998 ident: 10.1016/j.asoc.2016.02.027_bib0070 article-title: A genetic algorithm for the multidimensional knapsack problem publication-title: J. Heuristics doi: 10.1023/A:1009642405419 – volume: 4 start-page: 37 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0045 article-title: Overview of the algorithms for solving the multidimensional knapsack problems publication-title: Adv. Stud. Biol. – volume: 14 start-page: 66 year: 2014 ident: 10.1016/j.asoc.2016.02.027_bib0120 article-title: Improved binary artificial fish swarm algorithm for the 0–1 multidimensional knapsack problems publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2013.09.002 – volume: 144 start-page: 581 year: 2003 ident: 10.1016/j.asoc.2016.02.027_bib0080 article-title: Genetic algorithms with double strings for 0–1 programming problems publication-title: Eur. J. Oper. Res. doi: 10.1016/S0377-2217(02)00149-2 – volume: 26 start-page: 378 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0150 article-title: Self-adaptive check and repair operator-based particle swarm optimization for the multidimensional knapsack problem publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2014.10.030 – volume: 186 start-page: 63 year: 2008 ident: 10.1016/j.asoc.2016.02.027_bib0050 article-title: A dynamic programming based reduction procedure for the multidimensional 0–1 knapsack problem publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2006.02.058 – year: 2013 ident: 10.1016/j.asoc.2016.02.027_bib0130 – volume: 62 start-page: 2517 year: 2014 ident: 10.1016/j.asoc.2016.02.027_bib0015 article-title: Optimal design of cosine modulated nonuniform linear phase FIR filter bank via both stretching and shifting frequency response of single prototype filter publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2014.2312326 – volume: 41 start-page: 3712 year: 2014 ident: 10.1016/j.asoc.2016.02.027_bib0105 article-title: An improved firefly algorithm for solving dynamic multidimensional knapsack problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2013.11.040 – volume: 98 start-page: 1 year: 2014 ident: 10.1016/j.asoc.2016.02.027_bib0025 article-title: Optimal design of Hermitian transform and vectors of both mask and window coefficients for denoising applications with both unknown noise characteristics and distortions publication-title: Signal Process. doi: 10.1016/j.sigpro.2013.11.018 – volume: 155 start-page: 1 year: 2004 ident: 10.1016/j.asoc.2016.02.027_bib0030 article-title: The multidimensional 0–1 knapsack problem: an overview publication-title: Eur. J. Oper. Res. doi: 10.1016/S0377-2217(03)00274-1 – volume: 3 start-page: 443 year: 2008 ident: 10.1016/j.asoc.2016.02.027_bib0075 article-title: A hybrid genetic algorithm for the multidimensional knapsack problem publication-title: Int. J. Contemp. Math. Sci. – start-page: 358 year: 2007 ident: 10.1016/j.asoc.2016.02.027_bib0095 article-title: Particle swarm optimization for the multidimensional knapsack problem – volume: 57 start-page: 109 year: 2009 ident: 10.1016/j.asoc.2016.02.027_bib0185 article-title: Omitting meaningless digits in point estimates: the probability guarantee of leading-digit rules publication-title: Oper. Res. doi: 10.1287/opre.1080.0529 – volume: 29 start-page: 288 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0115 article-title: An effective hybrid harmony search-based algorithm for solving multidimensional knapsack problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.01.022 – volume: 48 start-page: 550 year: 2002 ident: 10.1016/j.asoc.2016.02.027_bib0035 article-title: An approximate dynamic programming approach to multidimensional knapsack problems publication-title: Manag. Sci. doi: 10.1287/mnsc.48.4.550.208 – start-page: 328 year: 2001 ident: 10.1016/j.asoc.2016.02.027_bib0060 article-title: A hybrid approach for the 0–1 multidimensional knapsack problem – start-page: 21 year: 2005 ident: 10.1016/j.asoc.2016.02.027_bib0065 article-title: Solving the multidimensional knapsack problem using an evolutionary algorithm hybridized with branch and bound – volume: 2 start-page: 137 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0135 article-title: A survey of bio inspired optimization algorithms publication-title: Int. J. Soft Comput. Eng. – volume: 63 start-page: 7 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0180 article-title: Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2015.04.018 – volume: 218 start-page: 11042 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0100 article-title: A modified binary particle swarm optimization for knapsack problems publication-title: Appl. Math. Comput. doi: 10.1016/j.amc.2012.05.001 – volume: 31 start-page: 153 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0165 article-title: Artificial algae algorithm (AAA) for nonlinear global optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.03.003 – volume: 22 start-page: 250 year: 2010 ident: 10.1016/j.asoc.2016.02.027_bib0040 article-title: The multidimensional knapsack problem: structure and algorithms publication-title: INFORMS J. Comput. doi: 10.1287/ijoc.1090.0344 – volume: 106 start-page: 659 year: 1998 ident: 10.1016/j.asoc.2016.02.027_bib0085 article-title: An efficient tabu search approach for the 0–1 multidimensional knapsack problem publication-title: Eur. J. Oper. Res. doi: 10.1016/S0377-2217(97)00296-8 – volume: 63 start-page: 7 year: 2015 ident: 10.1016/j.asoc.2016.02.027_bib0110 article-title: Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2015.04.018 – volume: 38 start-page: 1338 year: 2014 ident: 10.1016/j.asoc.2016.02.027_bib0145 article-title: Particle swarm optimization with time-varying acceleration coefficients for the multidimensional knapsack problem publication-title: Appl. Math. Model. doi: 10.1016/j.apm.2013.08.009 – year: 2005 ident: 10.1016/j.asoc.2016.02.027_bib0170 – volume: 60 start-page: 489 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0020 article-title: Filtering in rotated time-frequency domains with unknown noise statistics publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2011.2171956 – volume: 16 start-page: 320 year: 2007 ident: 10.1016/j.asoc.2016.02.027_bib0090 article-title: Simulated annealing for the 0/1 multidimensional knapsack problem publication-title: Numer. Math. Engl. Ser. – start-page: 4104 year: 1997 ident: 10.1016/j.asoc.2016.02.027_bib0140 article-title: A discrete binary version of the particle swarm algorithm – volume: 34 start-page: 161 year: 1987 ident: 10.1016/j.asoc.2016.02.027_bib0175 article-title: A heuristic solution procedure for the multiconstraint zero-one knapsack problem publication-title: Nav. Res. Logist. doi: 10.1002/1520-6750(198704)34:2<161::AID-NAV3220340203>3.0.CO;2-A – volume: 39 start-page: 2111 year: 2012 ident: 10.1016/j.asoc.2016.02.027_bib0055 article-title: Solving the multidimensional knapsack problems with generalized upper bound constraints by the adaptive memory projection method publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2011.10.016 – volume: 11 start-page: 1556 year: 2011 ident: 10.1016/j.asoc.2016.02.027_bib0160 article-title: Solving 0–1 knapsack problem by a novel global harmony search algorithm publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2010.07.019 – volume: 9 start-page: 588 year: 2013 ident: 10.1016/j.asoc.2016.02.027_bib0005 article-title: Efficient complex-valued finite word length allpass rational IIR PCLS filter design via functional inequality constrained integer programming with bit plane searching technique publication-title: Mediterr. J. Electron. Commun. – volume: 232 start-page: 58 year: 2013 ident: 10.1016/j.asoc.2016.02.027_bib0155 article-title: An improved adaptive binary harmony search algorithm publication-title: Inf. Sci. doi: 10.1016/j.ins.2012.12.043 |
| SSID | ssj0016928 |
| Score | 2.4253185 |
| Snippet | [Display omitted]
•A novel binary artificial algae algorithm is proposed for solving MKPs.•The method is composed of discrete process, repair operators and... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 583 |
| SubjectTerms | Artificial algae algorithm Elite local search Multidimensional knapsack problem Pseudo-utility ratio |
| Title | Binary artificial algae algorithm for multidimensional knapsack problems |
| URI | https://dx.doi.org/10.1016/j.asoc.2016.02.027 |
| Volume | 43 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Baden-Württemberg Complete Freedom Collection (Elsevier) customDbUrl: eissn: 1872-9681 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016928 issn: 1568-4946 databaseCode: GBLVA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Complete Freedom Collection [SCCMFC] customDbUrl: eissn: 1872-9681 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016928 issn: 1568-4946 databaseCode: ACRLP dateStart: 20010601 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals customDbUrl: eissn: 1872-9681 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016928 issn: 1568-4946 databaseCode: AIKHN dateStart: 20010601 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Science Direct customDbUrl: eissn: 1872-9681 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016928 issn: 1568-4946 databaseCode: .~1 dateStart: 20010601 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVLSH databaseName: Elsevier Journals customDbUrl: mediaType: online eissn: 1872-9681 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0016928 issn: 1568-4946 databaseCode: AKRWK dateStart: 20010601 isFulltext: true providerName: Library Specific Holdings |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEF6KXrz4Fuuj7MGbrH1ks7s51mKJryJqobeQfQRrNS22Xv3tziSboiA9CCHZhB3YHTbzgJnvI-Qs0y7TYAUZ-G_NuEoNU05FTEcWvLu2gbDY4Hw_EPGQ34zCUY30ql4YLKv0tr-06YW19l-aXpvN2XjcfILMQ_GIizaiRkmFiJ-cS2QxuPhalnm0RVTwq-JkhrN940xZ45WCBrC8SxS4ncgs85dz-uFw-ttk00eKtFsuZofUXL5LtioWBup_yj0SXxYttRRXXcJBUOzPcHifQur_8k4hMKVF5aBFLP8Sh4NO8nQ2T82Eek6Z-T4Z9q-eezHz_AjMwI4XzEE4IYQSsEWIU1Ips8DqzBmnubXaudQFugXD1Moo40JloZCuSHCM0QYitwOylk9zd0hooHQrNJnMOhEIc6O5sqGKjJKdEBIQXiftSjGJ8eDhyGHxllRVYq8JKjNBZSatDlyyTs6XMrMSOmPl7LDSd_LrACRg21fIHf1T7phs4FtZ9XVC1hYfn-4U4ouFbhQHqEHWu73Huwd8Xt_Gg28pedLR |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEF5qPejFt1ife_AmsW2y2d0ctShR215sobcl-8JaTYutV3-7s8mmKEgPQgghmYHdYTMP-OYbhC6tNFaCFwwgfsuA8EwF3PAkkImG6C51RLVrcO71aTokj6N4VEOdqhfGwSq97y99euGt_Zumt2ZzNh43n6Hy4CQhtO1YoxiP1tA6iUPmKrDrryXOo02TYsCqkw6cuO-cKUFeGZjA4btoQdzpRsv8FZ1-RJz7HbTlU0V8U65mF9VMvoe2qzEM2P-V-yi9LXpqsVt2yQeBXYOGcfcp1P4v7xgyU1xAB7Uj8y-JOPAkz2bzTE2wHyozP0DD-7tBJw38gIRAwZYXgYF8glJOYYuQqGSM2UhLa5SRRGtpTGYi2YLHTLPEEsptTJkpKhylpILU7RDV82lujhCOuGzFyjIbJqBMlCRcxzxRnIUxVCCkgdqVYYTy7OFuiMWbqGBir8IZUzhjilYIF2ugq6XOrOTOWCkdV_YWv06AAOe-Qu_4n3oXaCMd9Lqi-9B_OkGb7ksJATtF9cXHpzmDZGMhz4vD9A2dldLR |
| 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=Binary+artificial+algae+algorithm+for+multidimensional+knapsack+problems&rft.jtitle=Applied+soft+computing&rft.au=Zhang%2C+Xuedong&rft.au=Wu%2C+Changzhi&rft.au=Li%2C+Jing&rft.au=Wang%2C+Xiangyu&rft.date=2016-06-01&rft.issn=1568-4946&rft.volume=43&rft.spage=583&rft.epage=595&rft_id=info:doi/10.1016%2Fj.asoc.2016.02.027&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_asoc_2016_02_027 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1568-4946&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1568-4946&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1568-4946&client=summon |