Improved particle swarm optimization algorithm based novel encoding and decoding schemes for flexible job shop scheduling problem

•Chain encoding scheme efficiently describes FJSP.•Novel decoding scheme makes further local searching with a decoding process.•Improved communication mechanism of PSO brings finer searching.•Critical path method promotes searching efficiency•Formalized parameter tuning helps determine appropriate p...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Computers & operations research Ročník 121; s. 104951
Hlavní autoři:	Ding, Haojie, Gu, Xingsheng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier Ltd 01.09.2020 Pergamon Press Inc
Témata:	Algorithms Chains Critical path Encoding and decoding schemes Encoding-Decoding Flexible job shop scheduling problem Innovations Job shop scheduling Job shops Local search Mathematical analysis Operations research Parameters Particle swarm optimization Particle swarm optimization algorithm Production scheduling Solution space Tuning Flexible job shop scheduling problem Local search Operations research Encoding and decoding schemes Particle swarm optimization algorithm
ISSN:	0305-0548, 1873-765X, 0305-0548
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	•Chain encoding scheme efficiently describes FJSP.•Novel decoding scheme makes further local searching with a decoding process.•Improved communication mechanism of PSO brings finer searching.•Critical path method promotes searching efficiency•Formalized parameter tuning helps determine appropriate parameter values. The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study of FJSP is important to remarkably direct actual manufacturing processes. The paper proposes an improved particle swarm optimization (PSO) algorithm for solving FJSP and obtains beneficial solutions by improvement on encoding/decoding scheme, communication mechanism between particles, and alternate rules of candidate machines of operations. The innovation of encoding/decoding scheme proposes a novel designed chain encoding scheme and a corresponding effective decoding scheme. The chain-based encoding scheme can reasonably convert FJSP to an appropriate operation linked list and the novel designed decoding scheme owns the capacity of further explorering the solution space. The improvement of traditional PSO focuses on the innovation of information communication between particles, besides the modification of algorithm architecture. The amelioration of rules on operated machine selection is carried out based on the critical path of operations research (OR). It promotes algorithm efficiency by only alternating the candidate machines of operations on the critical path. In addition, much parameters tuning work is involved in a series of experiments. The study proposes some tuning schemes of parameters with exact mathematical methods, and these schemes can effectively help find more appropriate parameters. The final experiment results prove that the improved PSO exhibits remarkable ability to solve FJSP.
AbstractList	•Chain encoding scheme efficiently describes FJSP.•Novel decoding scheme makes further local searching with a decoding process.•Improved communication mechanism of PSO brings finer searching.•Critical path method promotes searching efficiency•Formalized parameter tuning helps determine appropriate parameter values. The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study of FJSP is important to remarkably direct actual manufacturing processes. The paper proposes an improved particle swarm optimization (PSO) algorithm for solving FJSP and obtains beneficial solutions by improvement on encoding/decoding scheme, communication mechanism between particles, and alternate rules of candidate machines of operations. The innovation of encoding/decoding scheme proposes a novel designed chain encoding scheme and a corresponding effective decoding scheme. The chain-based encoding scheme can reasonably convert FJSP to an appropriate operation linked list and the novel designed decoding scheme owns the capacity of further explorering the solution space. The improvement of traditional PSO focuses on the innovation of information communication between particles, besides the modification of algorithm architecture. The amelioration of rules on operated machine selection is carried out based on the critical path of operations research (OR). It promotes algorithm efficiency by only alternating the candidate machines of operations on the critical path. In addition, much parameters tuning work is involved in a series of experiments. The study proposes some tuning schemes of parameters with exact mathematical methods, and these schemes can effectively help find more appropriate parameters. The final experiment results prove that the improved PSO exhibits remarkable ability to solve FJSP. The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study of FJSP is important to remarkably direct actual manufacturing processes. The paper proposes an improved particle swarm optimization (PSO) algorithm for solving FJSP and obtains beneficial solutions by improvement on encoding/decoding scheme, communication mechanism between particles, and alternate rules of candidate machines of operations. The innovation of encoding/decoding scheme proposes a novel designed chain encoding scheme and a corresponding effective decoding scheme. The chain-based encoding scheme can reasonably convert FJSP to an appropriate operation linked list and the novel designed decoding scheme owns the capacity of further explorering the solution space. The improvement of traditional PSO focuses on the innovation of information communication between particles, besides the modification of algorithm architecture. The amelioration of rules on operated machine selection is carried out based on the critical path of operations research (OR). It promotes algorithm efficiency by only alternating the candidate machines of operations on the critical path. In addition, much parameters tuning work is involved in a series of experiments. The study proposes some tuning schemes of parameters with exact mathematical methods, and these schemes can effectively help find more appropriate parameters. The final experiment results prove that the improved PSO exhibits remarkable ability to solve FJSP.
ArticleNumber	104951
Author	Ding, Haojie Gu, Xingsheng
Author_xml	– sequence: 1 givenname: Haojie surname: Ding fullname: Ding, Haojie email: hero_ding1978@163.com – sequence: 2 givenname: Xingsheng orcidid: 0000-0002-1082-4586 surname: Gu fullname: Gu, Xingsheng email: xsgu@ecust.edu.cn
BookMark	eNp9kD1P5DAQhi3ESSx79wPoLFFnz3biOBEVQsCthHQNSNdZ_piwjpI42F6-Ov75eVkqinVjjeZ9ZjTPKTqe_AQInVGyooTWv_uV8WHFCNvVVcvpEVrQRpSFqPm_Y7QgJeEF4VVzgk5j7El-gtEF-liPc_DPYPGsQnJmABxfVBixn5Mb3btKzk9YDY8-uLQZsVYxZ6dMDBgm462bHrGaLLbwVUSzgREi7nzA3QCvTueZvdc4bvz82bXbYRfMe3Nr_Il-dGqI8OvrX6KHm-v7qz_F3d_b9dXlXWFKLlJhmADNmpJqCqUVOt_GK61VA4zUuuZVy3jTdkoQVYNtLWuFaBjTAGC4BSiX6Hw_N-992kJMsvfbMOWVkvFshlactDlF9ykTfIwBOjkHN6rwJimRO9Oyl9m03JmWe9OZEd8Y49KnuBSUGw6SF3sS8uHPDoKMxmWtYF0Ak6T17gD9HwSwnX8
CitedBy_id	crossref_primary_10_1016_j_ijpe_2024_109163 crossref_primary_10_1155_2022_9191247 crossref_primary_10_3390_pr11061826 crossref_primary_10_3390_machines10080618 crossref_primary_10_1109_ACCESS_2020_3033002 crossref_primary_10_1016_j_engappai_2025_112096 crossref_primary_10_1016_j_eswa_2022_119474 crossref_primary_10_1016_j_engappai_2024_109557 crossref_primary_10_1016_j_eswa_2025_128708 crossref_primary_10_1109_TNNLS_2022_3208942 crossref_primary_10_1007_s12065_024_00976_x crossref_primary_10_1016_j_eswa_2025_129590 crossref_primary_10_1051_wujns_2022276531 crossref_primary_10_3390_app14104029 crossref_primary_10_1016_j_engappai_2025_111951 crossref_primary_10_1016_j_asoc_2025_112697 crossref_primary_10_1016_j_eswa_2022_119359 crossref_primary_10_1016_j_cor_2025_107027 crossref_primary_10_1016_j_swevo_2024_101836 crossref_primary_10_1016_j_eswa_2025_127496 crossref_primary_10_1016_j_cor_2023_106174 crossref_primary_10_1108_AA_12_2020_0196 crossref_primary_10_3390_app14062586 crossref_primary_10_1007_s40295_023_00381_z crossref_primary_10_1007_s00521_024_09654_6 crossref_primary_10_1007_s10696_022_09446_x crossref_primary_10_1016_j_cie_2024_110688 crossref_primary_10_1016_j_cie_2024_110004 crossref_primary_10_1109_TCYB_2022_3158334 crossref_primary_10_1016_j_cor_2022_105731 crossref_primary_10_1016_j_cor_2025_107139 crossref_primary_10_1016_j_cor_2025_107216 crossref_primary_10_1016_j_cor_2023_106365 crossref_primary_10_1108_IJWIS_09_2023_0147 crossref_primary_10_1016_j_ins_2025_122298 crossref_primary_10_1016_j_cor_2024_106785 crossref_primary_10_1016_j_ejor_2023_05_017 crossref_primary_10_3390_s23010090 crossref_primary_10_1093_jcde_qwad078 crossref_primary_10_3390_pr13051583 crossref_primary_10_3390_math9070768 crossref_primary_10_3390_machines12090666 crossref_primary_10_3390_pr10030571 crossref_primary_10_1016_j_jfranklin_2025_107944 crossref_primary_10_1155_2021_1520859 crossref_primary_10_1007_s10489_022_04213_9 crossref_primary_10_1007_s10878_021_00748_8 crossref_primary_10_1016_j_cie_2024_109903 crossref_primary_10_1155_2022_4212556 crossref_primary_10_3390_e27070662 crossref_primary_10_1016_j_cor_2021_105267 crossref_primary_10_1016_j_knosys_2021_107815 crossref_primary_10_1038_s41598_025_91140_7 crossref_primary_10_1016_j_cie_2020_106781 crossref_primary_10_1016_j_rcim_2022_102509 crossref_primary_10_1016_j_jmsy_2021_05_018 crossref_primary_10_1016_j_engappai_2025_110447 crossref_primary_10_1080_23302674_2023_2221072 crossref_primary_10_1111_exsy_13727 crossref_primary_10_1016_j_engappai_2021_104411 crossref_primary_10_1002_cpe_6348 crossref_primary_10_1016_j_eswa_2022_117182 crossref_primary_10_1080_0305215X_2024_2328191 crossref_primary_10_1016_j_knosys_2020_106602 crossref_primary_10_3233_JIFS_224021 crossref_primary_10_1016_j_cie_2025_111330 crossref_primary_10_1016_j_cor_2024_106885 crossref_primary_10_1016_j_asoc_2024_111932 crossref_primary_10_1016_j_ejor_2022_06_009 crossref_primary_10_1016_j_swevo_2025_101943 crossref_primary_10_1016_j_cie_2025_111533 crossref_primary_10_1016_j_eswa_2025_129467 crossref_primary_10_1016_j_knosys_2024_111940 crossref_primary_10_1016_j_asoc_2024_111937 crossref_primary_10_1016_j_cor_2025_107155 crossref_primary_10_3390_machines10111100 crossref_primary_10_1177_09544054221121921
Cites_doi	10.1016/j.cor.2009.07.002 10.1016/j.omega.2015.04.002 10.1016/j.cie.2005.01.018 10.1016/j.procs.2017.08.267 10.1109/TASE.2013.2274517 10.1016/j.cie.2007.08.008 10.1080/00207540701824845 10.1016/j.ijpe.2014.03.006 10.1109/TSMCC.2007.897494 10.1287/opre.8.4.487 10.1016/j.cor.2011.10.024 10.1007/s10845-015-1039-3 10.1016/j.cie.2016.12.020 10.7763/IJCTE.2010.V2.139 10.1007/BF01719451 10.1016/j.ejor.2006.04.007 10.1016/j.cor.2007.02.014 10.1007/s10845-017-1350-2 10.1016/j.ejor.2017.08.021 10.1016/j.cie.2006.09.002 10.1287/moor.1.2.117 10.15837/ijccc.2007.2.2350 10.1016/j.eswa.2015.06.004 10.1109/TCYB.2018.2817240 10.1016/j.compchemeng.2016.04.030 10.1007/BF02023073 10.1016/j.cie.2007.04.010
ContentType	Journal Article
Copyright	2020 Elsevier Ltd Copyright Pergamon Press Inc. Sep 2020
Copyright_xml	– notice: 2020 Elsevier Ltd – notice: Copyright Pergamon Press Inc. Sep 2020
DBID	AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D
DOI	10.1016/j.cor.2020.104951
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 Computer Science Business
EISSN	1873-765X 0305-0548
ExternalDocumentID	10_1016_j_cor_2020_104951 S030505482030068X
GroupedDBID	--K --M -~X .DC .~1 0R~ 186 1B1 1OL 1RT 1~. 1~5 29F 4.4 457 4G. 5GY 5VS 6J9 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAFJI AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN AAYOK ABAOU ABBOA ABEFU ABFNM ABFRF ABJNI ABMAC ABMMH ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFO ACGFS ACNCT ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADJOM ADMUD AEBSH AEFWE AEHXG AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHZHX AI. AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV AKYCK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOMHK AOUOD APLSM ARUGR ASPBG AVARZ AVWKF AXJTR AZFZN BKOJK BKOMP BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q G8K GBLVA GBOLZ HAMUX HVGLF HZ~ H~9 IHE J1W KOM LY1 M41 MHUIS MO0 MS~ O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ PRBVW Q38 R2- RIG ROL RPZ RXW SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SSO SSV SSW SSZ T5K TAE TN5 U5U UAO UPT VH1 WUQ XFK XPP ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABDPE ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD 7SC 8FD AFXIZ AGCQF AGRNS BNPGV JQ2 L7M L~C L~D SSH
ID	FETCH-LOGICAL-c357t-c27eb2831b1e3d7b87354bba8e206b65492589fa70a6ed9d2977822beeec5dee3
ISICitedReferencesCount	101
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000540716700002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0305-0548
IngestDate	Sat Jul 26 00:01:11 EDT 2025 Sat Nov 29 07:22:28 EST 2025 Tue Nov 18 22:34:36 EST 2025 Fri Feb 23 02:46:47 EST 2024
IsPeerReviewed	true
IsScholarly	true
Keywords	Flexible job shop scheduling problem Local search Operations research Encoding and decoding schemes Particle swarm optimization algorithm
Language	English
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c357t-c27eb2831b1e3d7b87354bba8e206b65492589fa70a6ed9d2977822beeec5dee3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-1082-4586
PQID	2505414509
PQPubID	45870
ParticipantIDs	proquest_journals_2505414509 crossref_primary_10_1016_j_cor_2020_104951 crossref_citationtrail_10_1016_j_cor_2020_104951 elsevier_sciencedirect_doi_10_1016_j_cor_2020_104951
PublicationCentury	2000
PublicationDate	2020-09-01
PublicationDateYYYYMMDD	2020-09-01
PublicationDate_xml	– month: 09 year: 2020 text: 2020-09-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	Computers & operations research
PublicationYear	2020
Publisher	Elsevier Ltd Pergamon Press Inc
Publisher_xml	– name: Elsevier Ltd – name: Pergamon Press Inc
References	Zhang, Ding, Zou, Qin, Fu (bib0046) 2019; 30 Gothwal, Raj (bib0017) 2018; 8 Mesghouni, Hammadi, Borne (bib0030) 1997; Vol. 1 Novara, Novas, Henning (bib0034) 2016; 93 Pezzella, Morganti, Ciaschetti (bib0037) 2008; 35 Buzatu, Fota, Lepadatescu, Duicu (bib0004) 2009 Rossi (bib0038) 2014; 153 Jia, Chen, Tang (bib0023) 2007 Li, Pan, Xie, Jia, Wang (bib0025) 2010; 2 Gao, Suganthan, Chua, Chong, Cai, Pan (bib0011) 2015; 42 Bratton, Kennedy (bib0003) 2007 Yao, Liu, Zhao, Ding (bib0044) 2019 Lu, Li, Gao, Liao, Yi (bib0029) 2017; 104 Gao, Yang, Zhou, Pan, Suganthan (bib0010) 2018; 49 Najid, Dauzere-Peres, Zaidat (bib0032) 2002; Vol. 5 Sha, Hsu (bib0039) 2006; 51 Kennedy (bib0024) 2010 Ong, Tay, Kwoh (bib0035) 2005 Pellerin, Perrier, Berthaut (bib0036) 2019 Defraeye, Van Nieuwenhuyse (bib0007) 2016; 58 Girish, Jawahar (bib0015) 2009 Gu, Gu, Cao, Gu (bib0018) 2010; 37 Liu, Abraham, Choi, Moon (bib0027) 2006 Xia, Wu (bib0043) 2005; 48 Yuan, Xu (bib0045) 2013; 12 Garey, Johnson, Sethi (bib0012) 1976; 1 Girish, Jawahar (bib0016) 2009; 47 Tay, Ho (bib0041) 2008; 54 Andrade-Pineda, Canca, Gonzalez-R, Calle (bib0001) 2019 Gao, Gen, Sun, Zhao (bib0009) 2007; 53 Hu, Zhou, Wei, Quay, Reddy, Tellez, Nam (bib0021) 2018 Deng, Gu (bib0008) 2012; 39 Wang, Sun (bib0042) 2009; 2 Brandimarte (bib0002) 1993; 41 Giffler, Thompson (bib0014) 1960; 8 Ho, Tay, Lai (bib0020) 2007; 179 Liouane, Saad, Hammadi, Borne (bib0026) 2007; 2 Chaouch, Driss, Ghedira (bib0005) 2017; 112 Hurink, Jurisch, Thole (bib0022) 1994; 15 Liu, Abraham, Grosan (bib0028) 2007; Vol. 1 Motaghedi-larijani, Sabri-laghaie, Heydari (bib0031) 2010 Zribi, Kacem, El Kamel, Borne (bib0047) 2007; 37 Clerc (bib0006) 2010; Vol. 93 Shen, Dauzère-Pérès, Neufeld (bib0040) 2018; 265 Ghosh, Nath, Sarkar (bib0013) 2015 Henchiri, Ennigrou (bib0019) 2013 Nouiri, Bekrar, Jemai, Niar, Ammari (bib0033) 2018; 29 Lu (10.1016/j.cor.2020.104951_bib0029) 2017; 104 Yuan (10.1016/j.cor.2020.104951_bib0045) 2013; 12 Defraeye (10.1016/j.cor.2020.104951_bib0007) 2016; 58 Kennedy (10.1016/j.cor.2020.104951_bib0024) 2010 Rossi (10.1016/j.cor.2020.104951_bib0038) 2014; 153 Garey (10.1016/j.cor.2020.104951_bib0012) 1976; 1 Chaouch (10.1016/j.cor.2020.104951_bib0005) 2017; 112 Zhang (10.1016/j.cor.2020.104951_bib0046) 2019; 30 Gao (10.1016/j.cor.2020.104951_bib0010) 2018; 49 Mesghouni (10.1016/j.cor.2020.104951_bib0030) 1997; Vol. 1 Tay (10.1016/j.cor.2020.104951_bib0041) 2008; 54 Brandimarte (10.1016/j.cor.2020.104951_bib0002) 1993; 41 Bratton (10.1016/j.cor.2020.104951_bib0003) 2007 Hurink (10.1016/j.cor.2020.104951_bib0022) 1994; 15 Xia (10.1016/j.cor.2020.104951_bib0043) 2005; 48 Hu (10.1016/j.cor.2020.104951_bib0021) 2018 Li (10.1016/j.cor.2020.104951_bib0025) 2010; 2 Gu (10.1016/j.cor.2020.104951_bib0018) 2010; 37 Liu (10.1016/j.cor.2020.104951_bib0027) 2006 Najid (10.1016/j.cor.2020.104951_bib0032) 2002; Vol. 5 Girish (10.1016/j.cor.2020.104951_bib0016) 2009; 47 Jia (10.1016/j.cor.2020.104951_bib0023) 2007 Buzatu (10.1016/j.cor.2020.104951_bib0004) 2009 Nouiri (10.1016/j.cor.2020.104951_bib0033) 2018; 29 Motaghedi-larijani (10.1016/j.cor.2020.104951_bib0031) 2010 Ong (10.1016/j.cor.2020.104951_bib0035) 2005 Liu (10.1016/j.cor.2020.104951_bib0028) 2007; Vol. 1 Gothwal (10.1016/j.cor.2020.104951_bib0017) 2018; 8 Deng (10.1016/j.cor.2020.104951_bib0008) 2012; 39 Gao (10.1016/j.cor.2020.104951_bib0009) 2007; 53 Andrade-Pineda (10.1016/j.cor.2020.104951_bib0001) 2019 Ghosh (10.1016/j.cor.2020.104951_bib0013) 2015 Yao (10.1016/j.cor.2020.104951_bib0044) 2019 Girish (10.1016/j.cor.2020.104951_bib0015) 2009 Ho (10.1016/j.cor.2020.104951_bib0020) 2007; 179 Liouane (10.1016/j.cor.2020.104951_bib0026) 2007; 2 Pellerin (10.1016/j.cor.2020.104951_bib0036) 2019 Giffler (10.1016/j.cor.2020.104951_bib0014) 1960; 8 Zribi (10.1016/j.cor.2020.104951_bib0047) 2007; 37 Novara (10.1016/j.cor.2020.104951_bib0034) 2016; 93 Clerc (10.1016/j.cor.2020.104951_bib0006) 2010; Vol. 93 Gao (10.1016/j.cor.2020.104951_bib0011) 2015; 42 Pezzella (10.1016/j.cor.2020.104951_bib0037) 2008; 35 Sha (10.1016/j.cor.2020.104951_bib0039) 2006; 51 Shen (10.1016/j.cor.2020.104951_bib0040) 2018; 265 Wang (10.1016/j.cor.2020.104951_bib0042) 2009; 2 Henchiri (10.1016/j.cor.2020.104951_bib0019) 2013
References_xml	– volume: 58 start-page: 4 year: 2016 end-page: 25 ident: bib0007 article-title: Staffing and scheduling under nonstationary demand for service: a literature review publication-title: Omega – start-page: 385 year: 2013 end-page: 394 ident: bib0019 article-title: Particle swarm optimization combined with tabu search in a multi-agent model for flexible job shop problem publication-title: International Conference in Swarm Intelligence – volume: 35 start-page: 3202 year: 2008 end-page: 3212 ident: bib0037 article-title: A genetic algorithm for the flexible job-shop scheduling problem publication-title: Comput. Oper.. Res. – volume: 2 start-page: 174 year: 2007 end-page: 184 ident: bib0026 article-title: Ant systems & local search optimization for flexible job shop scheduling production publication-title: Int. J. Comput. Commun. Control – volume: 41 start-page: 157 year: 1993 end-page: 183 ident: bib0002 article-title: Routing and scheduling in a flexible job shop by tabu search publication-title: Ann. Oper. Res. – volume: 15 start-page: 205 year: 1994 end-page: 215 ident: bib0022 article-title: Tabu search for the job-shop scheduling problem with multi-purpose machines publication-title: Opera.-Res.-Spektrum – volume: 2 start-page: 189 year: 2010 ident: bib0025 article-title: A hybrid particle swarm optimization and tabu search algorithm for flexible job-shop scheduling problem publication-title: Int. J. Comput. Theory Eng. – volume: Vol. 1 start-page: 138 year: 2007 end-page: 145 ident: bib0028 article-title: A novel variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems publication-title: 2007 2nd International Conference on Digital Information Management – start-page: 442 year: 2005 end-page: 455 ident: bib0035 article-title: Applying the clonal selection principle to find flexible job-shop schedules publication-title: International Conference on Artificial Immune Systems – volume: 42 start-page: 7652 year: 2015 end-page: 7663 ident: bib0011 article-title: A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion publication-title: Expert Syst. Appl. – start-page: 60 year: 2015 end-page: 63 ident: bib0013 article-title: Pso algorithm with self tuned parameter for efficient routing in vlsi design publication-title: Proceedings of SSRG-IJECE International Conference on Futuristic Trends in Computing and Communication – volume: 51 start-page: 791 year: 2006 end-page: 808 ident: bib0039 article-title: A hybrid particle swarm optimization for job shop scheduling problem publication-title: Comput. Ind. Eng. – volume: 153 start-page: 253 year: 2014 end-page: 267 ident: bib0038 article-title: Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships publication-title: Int. J. Prod. Econ. – volume: 30 start-page: 1809 year: 2019 end-page: 1830 ident: bib0046 article-title: Review of job shop scheduling research and its new perspectives under industry 4.0 publication-title: J. Intell. Manuf. – volume: 37 start-page: 652 year: 2007 end-page: 661 ident: bib0047 article-title: Assignment and scheduling in flexible job-shops by hierarchical optimization publication-title: IEEE Trans. Syst. Man Cybernet. Part C (Appl. Rev.) – volume: 8 start-page: 487 year: 1960 end-page: 503 ident: bib0014 article-title: Algorithms for solving production-scheduling problems publication-title: Oper Res – start-page: 1 year: 2019 end-page: 31 ident: bib0001 article-title: Scheduling a dual-resource flexible job shop with makespan and due date-related criteria publication-title: Ann. Oper. Res. – year: 2019 ident: bib0036 article-title: A survey of hybrid metaheuristics for the resource-constrained project scheduling problem publication-title: Eur. J. Oper. Res. – volume: 1 start-page: 117 year: 1976 end-page: 129 ident: bib0012 article-title: The complexity of flowshop and jobshop scheduling publication-title: Math. Oper. Res. – year: 2010 ident: bib0031 article-title: Solving flexible job shop scheduling with multi objective approach publication-title: Int. J. Ind. Eng. Product. Res. – start-page: 298 year: 2009 end-page: 303 ident: bib0015 article-title: A particle swarm optimization algorithm for flexible job shop scheduling problem publication-title: 2009 IEEE International Conference on Automation Science and Engineering – start-page: 760 year: 2010 end-page: 766 ident: bib0024 article-title: Particle swarm optimization publication-title: Encycl. Mach. Learn. – volume: Vol. 1 start-page: 720 year: 1997 end-page: 725 ident: bib0030 article-title: Evolution programs for job-shop scheduling publication-title: 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation – volume: 29 start-page: 603 year: 2018 end-page: 615 ident: bib0033 article-title: An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem publication-title: J. Intell. Manuf. – volume: 54 start-page: 453 year: 2008 end-page: 473 ident: bib0041 article-title: Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems publication-title: Comput. Ind. Eng. – volume: 179 start-page: 316 year: 2007 end-page: 333 ident: bib0020 article-title: An effective architecture for learning and evolving flexible job-shop schedules publication-title: Eur. J. Oper. Res. – start-page: 139 year: 2009 end-page: 142 ident: bib0004 article-title: Modelling by finite element of the part-tool flexible technological system deformations at superfinishing process publication-title: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases – volume: 47 start-page: 3891 year: 2009 end-page: 3917 ident: bib0016 article-title: Scheduling job shop associated with multiple routings with genetic and ant colony heuristics publication-title: Int. J. Prod. Res. – volume: 12 start-page: 336 year: 2013 end-page: 353 ident: bib0045 article-title: Multiobjective flexible job shop scheduling using memetic algorithms publication-title: IEEE Trans. Autom. Sci. Eng. – volume: 49 start-page: 1944 year: 2018 end-page: 1955 ident: bib0010 article-title: Flexible job-shop rescheduling for new job insertion by using discrete jaya algorithm publication-title: IEEE Trans Cybern – volume: 2 start-page: 312 year: 2009 end-page: 315 ident: bib0042 article-title: Design of flexible scheduling system based on an improved genetic algorithm publication-title: 2009 Second International Symposium on Computational Intelligence and Design – start-page: 2260 year: 2019 end-page: 2265 ident: bib0044 article-title: An improved UKPK-PSO algorithm inspired from block chain technology for flexible job shop scheduling problem publication-title: 2019 Chinese Control Conference (CCC) – volume: 37 start-page: 927 year: 2010 end-page: 937 ident: bib0018 article-title: A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem publication-title: Comput. Oper. Res. – volume: 8 start-page: 59 year: 2018 end-page: 78 ident: bib0017 article-title: Prioritising the performance measures of FMS using multi-criteria decision making approaches publication-title: Int. J. Proc. Manag. Benchmark. – volume: Vol. 5 start-page: 6 year: 2002 end-page: pp ident: bib0032 article-title: A modified simulated annealing method for flexible job shop scheduling problem publication-title: IEEE international conference on systems, man and cybernetics – start-page: 197 year: 2006 end-page: 204 ident: bib0027 article-title: Variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems publication-title: Asia-Pacific Conference on Simulated Evolution and Learning – start-page: 120 year: 2007 end-page: 127 ident: bib0003 article-title: Defining a standard for particle swarm optimization publication-title: 2007 IEEE swarm intelligence symposium – volume: 53 start-page: 149 year: 2007 end-page: 162 ident: bib0009 article-title: A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems publication-title: Comput. Ind. Eng. – volume: 104 start-page: 156 year: 2017 end-page: 174 ident: bib0029 article-title: An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times publication-title: Comput. Ind. Eng. – start-page: 132 year: 2018 end-page: 138 ident: bib0021 article-title: Interconnect optimization considering multiple critical paths publication-title: Proceedings of the 2018 International Symposium on Physical Design – volume: Vol. 93 year: 2010 ident: bib0006 article-title: Particle swarm optimization – volume: 265 start-page: 503 year: 2018 end-page: 516 ident: bib0040 article-title: Solving the flexible job shop scheduling problem with sequence-dependent setup times publication-title: Eur. J. Oper. Res. – start-page: 1587 year: 2007 end-page: 1592 ident: bib0023 article-title: An improved particle swarm optimization for multi-objective flexible job-shop scheduling problem publication-title: 2007 IEEE International Conference on Grey Systems and Intelligent Services – volume: 39 start-page: 2152 year: 2012 end-page: 2160 ident: bib0008 article-title: A hybrid discrete differential evolution algorithm for the no-idle permutation flow shop scheduling problem with makespan criterion publication-title: Comput. Oper.. Res. – volume: 93 start-page: 101 year: 2016 end-page: 117 ident: bib0034 article-title: A novel constraint programming model for large-scale scheduling problems in multiproduct multistage batch plants: limited resources and campaign-based operation publication-title: Comput. Chem. Eng. – volume: 48 start-page: 409 year: 2005 end-page: 425 ident: bib0043 article-title: An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems publication-title: Comput. Ind. Eng. – volume: 112 start-page: 296 year: 2017 end-page: 305 ident: bib0005 article-title: A modified ant colony optimization algorithm for the distributed job shop scheduling problem publication-title: Procedia Comput. Sci. – start-page: 197 year: 2006 ident: 10.1016/j.cor.2020.104951_bib0027 article-title: Variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems – volume: Vol. 5 start-page: 6 year: 2002 ident: 10.1016/j.cor.2020.104951_bib0032 article-title: A modified simulated annealing method for flexible job shop scheduling problem – volume: 37 start-page: 927 issue: 5 year: 2010 ident: 10.1016/j.cor.2020.104951_bib0018 article-title: A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2009.07.002 – volume: 58 start-page: 4 year: 2016 ident: 10.1016/j.cor.2020.104951_bib0007 article-title: Staffing and scheduling under nonstationary demand for service: a literature review publication-title: Omega doi: 10.1016/j.omega.2015.04.002 – volume: 48 start-page: 409 issue: 2 year: 2005 ident: 10.1016/j.cor.2020.104951_bib0043 article-title: An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2005.01.018 – start-page: 298 year: 2009 ident: 10.1016/j.cor.2020.104951_bib0015 article-title: A particle swarm optimization algorithm for flexible job shop scheduling problem – start-page: 120 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0003 article-title: Defining a standard for particle swarm optimization – start-page: 139 year: 2009 ident: 10.1016/j.cor.2020.104951_bib0004 article-title: Modelling by finite element of the part-tool flexible technological system deformations at superfinishing process – volume: 112 start-page: 296 year: 2017 ident: 10.1016/j.cor.2020.104951_bib0005 article-title: A modified ant colony optimization algorithm for the distributed job shop scheduling problem publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2017.08.267 – volume: 12 start-page: 336 issue: 1 year: 2013 ident: 10.1016/j.cor.2020.104951_bib0045 article-title: Multiobjective flexible job shop scheduling using memetic algorithms publication-title: IEEE Trans. Autom. Sci. Eng. doi: 10.1109/TASE.2013.2274517 – volume: 54 start-page: 453 issue: 3 year: 2008 ident: 10.1016/j.cor.2020.104951_bib0041 article-title: Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2007.08.008 – volume: 47 start-page: 3891 issue: 14 year: 2009 ident: 10.1016/j.cor.2020.104951_bib0016 article-title: Scheduling job shop associated with multiple routings with genetic and ant colony heuristics publication-title: Int. J. Prod. Res. doi: 10.1080/00207540701824845 – start-page: 442 year: 2005 ident: 10.1016/j.cor.2020.104951_bib0035 article-title: Applying the clonal selection principle to find flexible job-shop schedules – volume: 153 start-page: 253 year: 2014 ident: 10.1016/j.cor.2020.104951_bib0038 article-title: Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships publication-title: Int. J. Prod. Econ. doi: 10.1016/j.ijpe.2014.03.006 – volume: 37 start-page: 652 issue: 4 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0047 article-title: Assignment and scheduling in flexible job-shops by hierarchical optimization publication-title: IEEE Trans. Syst. Man Cybernet. Part C (Appl. Rev.) doi: 10.1109/TSMCC.2007.897494 – volume: 8 start-page: 487 issue: 4 year: 1960 ident: 10.1016/j.cor.2020.104951_bib0014 article-title: Algorithms for solving production-scheduling problems publication-title: Oper Res doi: 10.1287/opre.8.4.487 – year: 2019 ident: 10.1016/j.cor.2020.104951_bib0036 article-title: A survey of hybrid metaheuristics for the resource-constrained project scheduling problem publication-title: Eur. J. Oper. Res. – volume: 39 start-page: 2152 issue: 9 year: 2012 ident: 10.1016/j.cor.2020.104951_bib0008 article-title: A hybrid discrete differential evolution algorithm for the no-idle permutation flow shop scheduling problem with makespan criterion publication-title: Comput. Oper.. Res. doi: 10.1016/j.cor.2011.10.024 – volume: 29 start-page: 603 issue: 3 year: 2018 ident: 10.1016/j.cor.2020.104951_bib0033 article-title: An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem publication-title: J. Intell. Manuf. doi: 10.1007/s10845-015-1039-3 – volume: 104 start-page: 156 year: 2017 ident: 10.1016/j.cor.2020.104951_bib0029 article-title: An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2016.12.020 – year: 2010 ident: 10.1016/j.cor.2020.104951_bib0031 article-title: Solving flexible job shop scheduling with multi objective approach publication-title: Int. J. Ind. Eng. Product. Res. – start-page: 385 year: 2013 ident: 10.1016/j.cor.2020.104951_bib0019 article-title: Particle swarm optimization combined with tabu search in a multi-agent model for flexible job shop problem – volume: 2 start-page: 189 issue: 2 year: 2010 ident: 10.1016/j.cor.2020.104951_bib0025 article-title: A hybrid particle swarm optimization and tabu search algorithm for flexible job-shop scheduling problem publication-title: Int. J. Comput. Theory Eng. doi: 10.7763/IJCTE.2010.V2.139 – volume: 2 start-page: 312 year: 2009 ident: 10.1016/j.cor.2020.104951_bib0042 article-title: Design of flexible scheduling system based on an improved genetic algorithm – start-page: 60 year: 2015 ident: 10.1016/j.cor.2020.104951_bib0013 article-title: Pso algorithm with self tuned parameter for efficient routing in vlsi design – volume: 15 start-page: 205 issue: 4 year: 1994 ident: 10.1016/j.cor.2020.104951_bib0022 article-title: Tabu search for the job-shop scheduling problem with multi-purpose machines publication-title: Opera.-Res.-Spektrum doi: 10.1007/BF01719451 – volume: 8 start-page: 59 issue: 1 year: 2018 ident: 10.1016/j.cor.2020.104951_bib0017 article-title: Prioritising the performance measures of FMS using multi-criteria decision making approaches publication-title: Int. J. Proc. Manag. Benchmark. – volume: 179 start-page: 316 issue: 2 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0020 article-title: An effective architecture for learning and evolving flexible job-shop schedules publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2006.04.007 – volume: Vol. 1 start-page: 720 year: 1997 ident: 10.1016/j.cor.2020.104951_bib0030 article-title: Evolution programs for job-shop scheduling – volume: 35 start-page: 3202 issue: 10 year: 2008 ident: 10.1016/j.cor.2020.104951_bib0037 article-title: A genetic algorithm for the flexible job-shop scheduling problem publication-title: Comput. Oper.. Res. doi: 10.1016/j.cor.2007.02.014 – volume: 30 start-page: 1809 issue: 4 year: 2019 ident: 10.1016/j.cor.2020.104951_bib0046 article-title: Review of job shop scheduling research and its new perspectives under industry 4.0 publication-title: J. Intell. Manuf. doi: 10.1007/s10845-017-1350-2 – start-page: 1 year: 2019 ident: 10.1016/j.cor.2020.104951_bib0001 article-title: Scheduling a dual-resource flexible job shop with makespan and due date-related criteria publication-title: Ann. Oper. Res. – volume: 265 start-page: 503 issue: 2 year: 2018 ident: 10.1016/j.cor.2020.104951_bib0040 article-title: Solving the flexible job shop scheduling problem with sequence-dependent setup times publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2017.08.021 – volume: 51 start-page: 791 issue: 4 year: 2006 ident: 10.1016/j.cor.2020.104951_bib0039 article-title: A hybrid particle swarm optimization for job shop scheduling problem publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2006.09.002 – start-page: 760 year: 2010 ident: 10.1016/j.cor.2020.104951_bib0024 article-title: Particle swarm optimization publication-title: Encycl. Mach. Learn. – volume: Vol. 93 year: 2010 ident: 10.1016/j.cor.2020.104951_bib0006 – volume: 1 start-page: 117 issue: 2 year: 1976 ident: 10.1016/j.cor.2020.104951_bib0012 article-title: The complexity of flowshop and jobshop scheduling publication-title: Math. Oper. Res. doi: 10.1287/moor.1.2.117 – start-page: 2260 year: 2019 ident: 10.1016/j.cor.2020.104951_bib0044 article-title: An improved UKPK-PSO algorithm inspired from block chain technology for flexible job shop scheduling problem – volume: 2 start-page: 174 issue: 2 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0026 article-title: Ant systems & local search optimization for flexible job shop scheduling production publication-title: Int. J. Comput. Commun. Control doi: 10.15837/ijccc.2007.2.2350 – volume: 42 start-page: 7652 issue: 21 year: 2015 ident: 10.1016/j.cor.2020.104951_bib0011 article-title: A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2015.06.004 – volume: 49 start-page: 1944 issue: 5 year: 2018 ident: 10.1016/j.cor.2020.104951_bib0010 article-title: Flexible job-shop rescheduling for new job insertion by using discrete jaya algorithm publication-title: IEEE Trans Cybern doi: 10.1109/TCYB.2018.2817240 – volume: Vol. 1 start-page: 138 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0028 article-title: A novel variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems – start-page: 1587 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0023 article-title: An improved particle swarm optimization for multi-objective flexible job-shop scheduling problem – volume: 93 start-page: 101 year: 2016 ident: 10.1016/j.cor.2020.104951_bib0034 article-title: A novel constraint programming model for large-scale scheduling problems in multiproduct multistage batch plants: limited resources and campaign-based operation publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2016.04.030 – start-page: 132 year: 2018 ident: 10.1016/j.cor.2020.104951_bib0021 article-title: Interconnect optimization considering multiple critical paths – volume: 41 start-page: 157 issue: 3 year: 1993 ident: 10.1016/j.cor.2020.104951_bib0002 article-title: Routing and scheduling in a flexible job shop by tabu search publication-title: Ann. Oper. Res. doi: 10.1007/BF02023073 – volume: 53 start-page: 149 issue: 1 year: 2007 ident: 10.1016/j.cor.2020.104951_bib0009 article-title: A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2007.04.010
SSID	ssj0000721
Score	2.615314
Snippet	•Chain encoding scheme efficiently describes FJSP.•Novel decoding scheme makes further local searching with a decoding process.•Improved communication... The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study...
SourceID	proquest crossref elsevier
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	104951
SubjectTerms	Algorithms Chains Critical path Encoding and decoding schemes Encoding-Decoding Flexible job shop scheduling problem Innovations Job shop scheduling Job shops Local search Mathematical analysis Operations research Parameters Particle swarm optimization Particle swarm optimization algorithm Production scheduling Solution space Tuning
Title	Improved particle swarm optimization algorithm based novel encoding and decoding schemes for flexible job shop scheduling problem
URI	https://dx.doi.org/10.1016/j.cor.2020.104951 https://www.proquest.com/docview/2505414509
Volume	121
WOSCitedRecordID	wos000540716700002&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 customDbUrl: eissn: 1873-765X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000721 issn: 0305-0548 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3Nb9MwFLdKhxAc-ChDbAzkAyeiSPl2fJzYxuAwcRhSb1Ecu7RVm0RJO3bdf75n5zktnTaxA5eodWLLyvvl-T37vd8j5HMaFUUae5Gb-1y6URwINw194RY8h_VIH5wluSk2wS4u0vGY_xwM1jYX5mrByjK9vub1fxU1tIGwdersI8TdDwoN8BuEDlcQO1z_SfDdNgHYkTXedNo_ebN0KlAOS8y6dPLF76qZraZLRy9j0imhx8LRpJbSZi1KhX_A_1Wa0kkHJE40f6ZOtppXwmmnVW3uyjUmtZviNNv2ri0a0RqIVbVqMPQOSYb6zegTrK1ynlfzWQ-2b2vdNta7-VOFayxuUYA_amOw-tQsHSEYd5SavdrtMqNRcYJXyDvm2Ts6vdtemININH9rYI6l8dm_-bN31rU-2tAGss0zGCLTQ2TdEE_IHsCRp0Oyd_z9dPxjs4Qzk7DXz9seh5vAwJ153GfQ7Cztxl65fE1eoqNBjzsMvCEDVY7IM5vnMCKvrGgoqvcRebFFTvmW3FggUQskaoBEt4FEeyBRAyRqgEQtkCgAiVogUQQSBSBRCyQKQKIaSHQDJIpA2ie_zk4vv567WLDDLcKYrdwiYEoE-lv3VSiZSFkYR0LkqQq8RCSaDDBO-SRnXp4oyWUAzgcYqEIpVcRSqfAdGZZVqd4TGiQTKZknIhlyMCILEfqTmDGZBFyGMmEHxLNvPSuQzV4XVVlk90r7gHzpu9QdlctDD0dWlBnaop2NmQEsH-p2ZMWeoU5oM-1lRH4EpvnhY6bwgTzffExHZLhq1uojeVpcrWZt8wkhewtpkbhX
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=Improved+particle+swarm+optimization+algorithm+based+novel+encoding+and+decoding+schemes+for+flexible+job+shop+scheduling+problem&rft.jtitle=Computers+%26+operations+research&rft.au=Ding%2C+Haojie&rft.au=Gu%2C+Xingsheng&rft.date=2020-09-01&rft.issn=0305-0548&rft.volume=121&rft.spage=104951&rft_id=info:doi/10.1016%2Fj.cor.2020.104951&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_cor_2020_104951
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0305-0548&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0305-0548&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0305-0548&client=summon