An empirical performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problem

The Job-Shop Scheduling Problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Several GA-based approaches have been reported for the JSSP. Among them, there is a parameter-free genetic algorithm (PfGA) for JSSP proposed by Matsui et al., based on an e...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2007 IEEE Congress on Evolutionary Computation S. 3796 - 3803
Hauptverfasser: Matsui, S., Yamada, S.
Format: Tagungsbericht
Sprache:Englisch
Japanisch
Veröffentlicht: IEEE 01.09.2007
Schlagworte:
Algorithm design and analysis
Biological cells
Decoding
Design engineering
Genetic algorithms
History
Job shop scheduling
Power engineering and energy
Production
Simulated annealing
ISBN:1424413397, 9781424413393
ISSN:1089-778X
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract The Job-Shop Scheduling Problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Several GA-based approaches have been reported for the JSSP. Among them, there is a parameter-free genetic algorithm (PfGA) for JSSP proposed by Matsui et al., based on an extended version of PfGA, which uses random keys for representing permutation of operations in jobs, and uses a hybrid scheduling for decoding a permutation into a schedule. They reported that their algorithm performs well for typical benchmark problems, but the experiments were limited to a small number of problem instances. This paper shows the results of an empirical performance evaluation of the GA for a wider range of problem instances. The results show that the GA performs well for many problem instances, and the performance can be improved greatly by increasing the number of subpopulations in the parallel distributed version.
AbstractList The Job-Shop Scheduling Problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Several GA-based approaches have been reported for the JSSP. Among them, there is a parameter-free genetic algorithm (PfGA) for JSSP proposed by Matsui et al., based on an extended version of PfGA, which uses random keys for representing permutation of operations in jobs, and uses a hybrid scheduling for decoding a permutation into a schedule. They reported that their algorithm performs well for typical benchmark problems, but the experiments were limited to a small number of problem instances. This paper shows the results of an empirical performance evaluation of the GA for a wider range of problem instances. The results show that the GA performs well for many problem instances, and the performance can be improved greatly by increasing the number of subpopulations in the parallel distributed version.
Author Yamada, S.
Matsui, S.
Author_xml – sequence: 1
  givenname: S.
  surname: Matsui
  fullname: Matsui, S.
  organization: Central Res. Inst. of Electr. Power Ind., Tokyo
– sequence: 2
  givenname: S.
  surname: Yamada
  fullname: Yamada, S.
BookMark eNo9kD1rwzAYhFWaQpM0e6GL_oBTfdmSxmDSDwh0aaFbeC2_ShRsychOof--gZbecvcMd8MtyCymiITcc7bmnNnHeluvBWN6rZRQtiqvyIJfkuJSMXb9D9LqGZlzZmyhtfm8JatxPLGLVKm4VnMSNpFiP4QcHHR0wOxT7iE6pPgF3RmmkCJNngIdIEOPE-bCZ0R6wIhTcBS6Q8phOvb00qSn1BTjMQ10dEdsz12IBzrk1HTY35EbD92Iqz9fko-n7Xv9Uuzenl_rza4IQrOpAFcZbbkrhWdlaZXlwFvjvHCaNxwYOqmatvWyRKelEQa0RN22yrHKKFHJJXn43Q2IuB9y6CF_7_9ukj_M2ly9
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CEC.2007.4424965
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Xplore
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
EISBN 1424413400
9781424413409
EndPage 3803
ExternalDocumentID 4424965
Genre orig-research
GroupedDBID -~X
.DC
0R~
29I
4.4
5GY
5VS
6IE
6IF
6IK
6IL
6IN
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABJNI
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ADZIZ
AENEX
AETIX
AGQYO
AGSQL
AHBIQ
AI.
AIBXA
AKJIK
AKQYR
ALLEH
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
CS3
EBS
EJD
HZ~
H~9
IEGSK
IFIPE
IFJZH
IPLJI
JAVBF
LAI
M43
O9-
OCL
P2P
PQQKQ
RIA
RIE
RIL
RNS
TN5
VH1
ID FETCH-LOGICAL-i270t-ac68791c52f0559491a1d8cf2c71b1a0ec34bddf35ec73828a73e7dd4c0684263
IEDL.DBID RIE
ISBN 1424413397
9781424413393
ISICitedReferencesCount 2
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000256053702122&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1089-778X
IngestDate Wed Aug 27 01:41:41 EDT 2025
IsPeerReviewed true
IsScholarly true
Language English
Japanese
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i270t-ac68791c52f0559491a1d8cf2c71b1a0ec34bddf35ec73828a73e7dd4c0684263
PageCount 8
ParticipantIDs ieee_primary_4424965
PublicationCentury 2000
PublicationDate 2007-09-01
PublicationDateYYYYMMDD 2007-09-01
PublicationDate_xml – month: 09
  year: 2007
  text: 2007-09-01
  day: 01
PublicationDecade 2000
PublicationTitle 2007 IEEE Congress on Evolutionary Computation
PublicationTitleAbbrev CEC
PublicationYear 2007
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0000454174
ssj0014519
Score 1.6692027
Snippet The Job-Shop Scheduling Problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Several GA-based approaches have...
SourceID ieee
SourceType Publisher
StartPage 3796
SubjectTerms Algorithm design and analysis
Biological cells
Decoding
Design engineering
Genetic algorithms
History
Job shop scheduling
Power engineering and energy
Production
Simulated annealing
Title An empirical performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problem
URI https://ieeexplore.ieee.org/document/4424965
WOSCitedRecordID wos000256053702122&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
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3PT8IwFMdfkHjQCwoYf6cHj062tqzr0RCIJ8JBE26kP2VGNjKGf7_tNkATL962NcuWps17r-99Pw_gQRKqsNtkAcaWB5QpEwjrghVKpMKRoaGVsmo2wabTZD7nsxY87rUwxpiq-Mw8-csql69ztfVHZQNKscebH8ERY3Gt1dqfp3iUXORdmSaD4LEpdXE9dx5kMt-JulxMVrMAPeupuSe7_GXIB6PxqAYbNh_71XWlMjqTzv9-9wz6B_Uemu3t0jm0TNaFzq59A2p2cxdOf7AIe5A-Z8is1mmFDEHrg54AHYDgKLdIIE8LX_kqmsAWxiC3Ar0QEonP97xIy-UKuTfRRy6DzTJfIxc9O2vmRe-oaV7Th7fJ-HX0EjR9GIIUs7AMhIoTxiM1xDZ0AQjlkYh0oixWLJKRCI0iVGptydAoRlwIJxgxTGuqQp_li8kFtLM8M5eAnHujiObajUjKhBKE60TGwlrj_BQRXkHPz-NiXaM2Fs0UXv_9-AZO6qNWX_J1C-2y2Jo7OFZfZbop7qv18Q0ClLaM
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ1NT8JAEIYniCbqBQWM3-7Bo5W2u7Dt0RAIRiQcMOFG9lNqpCWl-PvdbQto4sXbtk3TZrObmdmZ9xmAe46J8M0mc3xfhw6hQjlMm2CFYC58TxFXc543m6CjUTCdhuMKPGy1MEqpvPhMPdphnsuXiVjbo7IWIb7Fm-_BftsM3UKttT1RsTA5zzozZQ7BglOK8vrQ-JDBdCPrMlFZQQO0tKfyGm8ymG7Y6va6Bdqw_Nyvviu52enX_vfDJ9Dc6ffQeGuZTqGi4jrUNg0cULmf63D8g0bYgOgpRmqxjHJoCFruFAVohwRHiUYMWV74wtbRODpVCpk1aKWQiH2-J2mUzRfIvIk-Eu6s5skSmfjZ2DMre0dl-5omvPV7k-7AKTsxOJFP3cxhohPQ0BNtX7smBCGhxzwZCO0L6nGPuUpgwqXUuK0ExSaIYxQrKiURrs3zdfAZVOMkVueAjIMjsAylecIJZYLhUAa8w7RWxlNh7gU07DzOlgVsY1ZO4eXft-_gcDB5Hc6Gz6OXKzgqDl5tAdg1VLN0rW7gQHxl0Sq9zdfKN7GbudM
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%3Abook&rft.genre=proceeding&rft.title=2007+IEEE+Congress+on+Evolutionary+Computation&rft.atitle=An+empirical+performance+evaluation+of+a+parameter-free+genetic+algorithm+for+job-shop+scheduling+problem&rft.au=Matsui%2C+S.&rft.au=Yamada%2C+S.&rft.date=2007-09-01&rft.pub=IEEE&rft.isbn=9781424413393&rft.issn=1089-778X&rft.spage=3796&rft.epage=3803&rft_id=info:doi/10.1109%2FCEC.2007.4424965&rft.externalDocID=4424965
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1089-778X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1089-778X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1089-778X&client=summon