schliessen

Filtern

 

Bibliotheken

Efficient multi-objective evolutionary algorithm for job shop scheduling

F0; A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority... Full description

Journal Title: Chinese journal of mechanical engineering 2005, Vol.18 (4), p.494-497
Main Author: Lei, Deming
Format: Electronic Article Electronic Article
Language: English
Quelle: Alma/SFX Local Collection
Publisher: Institute of Automation,Shanghai Jiaotong University, Shanghai 200030, China
ID: ISSN: 1000-9345
Zum Text:
SendSend as email Add to Book BagAdd to Book Bag
Staff View
recordid: cdi_wanfang_journals_jxgcxb_e200504005
title: Efficient multi-objective evolutionary algorithm for job shop scheduling
format: Article
creator:
  • Lei, Deming
ispartof: Chinese journal of mechanical engineering, 2005, Vol.18 (4), p.494-497
description: F0; A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1000-9345
fulltext: fulltext
issn:
  • 1000-9345
  • 2192-8258
url: Link


@attributes
NO1
SEARCH_ENGINEprimo_central_multiple_fe
SEARCH_ENGINE_TYPEPrimo Central Search Engine
RANK1.8494998
LOCALfalse
PrimoNMBib
record
control
sourceidwanfang_jour_cross
recordidTN_cdi_wanfang_journals_jxgcxb_e200504005
sourceformatXML
sourcesystemPC
wanfj_idjxgcxb_e200504005
sourcerecordidjxgcxb_e200504005
originalsourceidFETCH-LOGICAL-c1665-3c5c3cb51acea092d6728f3deb3b98126d912f6c160f83816f9f99d32b1863b43
addsrcrecordideNotkD1PwzAQhi0EEqWwM3plSPBXjD2iqlBQEQvMlu3YqaM0ruKklH-Po7Lc6aTn7vQ-ANxjVFKJ8OPq_WNdEoSqErGSSXYBFgRLUghSiUuwwAihQlJWXYOblNo8cYzFAmzW3gcbXD_C_dSNoYimdXYMRwfdMXbTGGKvh1-ouyYOYdztoY8DbKOBaRcPMNmdq6cu9M0tuPK6S-7uvy_B98v6a7Uptp-vb6vnbWEx51VBbWWpNRXW1mkkSc2fiPC0doYaKTDhtcTE8wwjL6jA3EsvZU2JwYJTw-gSPJzv_uje675RbZyGPn9U7amxJ6PcLAGxXDKLzqwdYkqD8-owhH2OozBSszU1W1PzgkJMZWv0DxCiYDc
sourcetypeAggregation Database
isCDItrue
recordtypearticle
display
typearticle
titleEfficient multi-objective evolutionary algorithm for job shop scheduling
sourceAlma/SFX Local Collection
creatorLei, Deming
creatorcontribLei, Deming
descriptionF0; A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.
identifier
0ISSN: 1000-9345
1EISSN: 2192-8258
2DOI: 10.3901/CJME.2005.04.494
languageeng
publisherInstitute of Automation,Shanghai Jiaotong University, Shanghai 200030, China
ispartofChinese journal of mechanical engineering, 2005, Vol.18 (4), p.494-497
rightsCopyright © Wanfang Data Co. Ltd. All Rights Reserved.
lds50peer_reviewed
links
openurl$$Topenurl_article
openurlfulltext$$Topenurlfull_article
thumbnail$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/jxgcxb-e/jxgcxb-e.jpg
search
creatorcontribLei, Deming
title
0Efficient multi-objective evolutionary algorithm for job shop scheduling
1Chinese journal of mechanical engineering
descriptionF0; A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.
issn
01000-9345
12192-8258
fulltexttrue
rsrctypearticle
creationdate2005
recordtypearticle
recordideNotkD1PwzAQhi0EEqWwM3plSPBXjD2iqlBQEQvMlu3YqaM0ruKklH-Po7Lc6aTn7vQ-ANxjVFKJ8OPq_WNdEoSqErGSSXYBFgRLUghSiUuwwAihQlJWXYOblNo8cYzFAmzW3gcbXD_C_dSNoYimdXYMRwfdMXbTGGKvh1-ouyYOYdztoY8DbKOBaRcPMNmdq6cu9M0tuPK6S-7uvy_B98v6a7Uptp-vb6vnbWEx51VBbWWpNRXW1mkkSc2fiPC0doYaKTDhtcTE8wwjL6jA3EsvZU2JwYJTw-gSPJzv_uje675RbZyGPn9U7amxJ6PcLAGxXDKLzqwdYkqD8-owhH2OozBSszU1W1PzgkJMZWv0DxCiYDc
startdate2005
enddate2005
creatorLei, Deming
generalInstitute of Automation,Shanghai Jiaotong University, Shanghai 200030, China
scope
0AAYXX
1CITATION
22B.
34A8
492I
593N
6PSX
7TCJ
sort
creationdate2005
titleEfficient multi-objective evolutionary algorithm for job shop scheduling
authorLei, Deming
facets
frbrtype5
frbrgroupidcdi_FETCH-LOGICAL-c1665-3c5c3cb51acea092d6728f3deb3b98126d912f6c160f83816f9f99d32b1863b43
rsrctypearticles
prefilterarticles
languageeng
creationdate2005
toplevel
0peer_reviewed
1online_resources
creatorcontribLei, Deming
collection
0CrossRef
1Wanfang Data Journals - Hong Kong
2WANFANG Data Centre
3Wanfang Data Journals
4万方数据期刊 - 香港版
5China Online Journals (COJ)
6China Online Journals (COJ)
jtitleChinese journal of mechanical engineering
delivery
delcategoryRemote Search Resource
fulltextfulltext
addata
auLei, Deming
formatjournal
genrearticle
ristypeJOUR
atitleEfficient multi-objective evolutionary algorithm for job shop scheduling
jtitleChinese journal of mechanical engineering
date2005
risdate2005
volume18
issue4
spage494
epage497
pages494-497
issn1000-9345
eissn2192-8258
abstractF0; A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.
pubInstitute of Automation,Shanghai Jiaotong University, Shanghai 200030, China
doi10.3901/CJME.2005.04.494