A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems
Abstract: "The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous efforts using genetic algorithms for this task, and comparable...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Edinburgh
1993
|
Schriftenreihe: | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper
623 |
Schlagworte: | |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
LEADER | 00000nam a2200000 cb4500 | ||
---|---|---|---|
001 | BV010463139 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
007 | t | ||
008 | 951106s1993 |||| 00||| engod | ||
035 | |a (OCoLC)32307137 | ||
035 | |a (DE-599)BVBBV010463139 | ||
040 | |a DE-604 |b ger |e rakddb | ||
041 | 0 | |a eng | |
049 | |a DE-91G | ||
100 | 1 | |a Fang, Hsiao-Lan |e Verfasser |4 aut | |
245 | 1 | 0 | |a A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems |c Hsiao-Lan Fang, Peter Ross, and Dave Corne |
264 | 1 | |a Edinburgh |c 1993 | |
300 | |a 9 S. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 1 | |a University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |v 623 | |
520 | 3 | |a Abstract: "The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous efforts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderately well for the traveling salesman problem. It has the considerable merit that crossover will always produce legal schedules. A novel method for performance enhancement is examined based on dynamic sampling of the convergence rates in different parts of the genome. Our approach also promises to effectively address the open-shop scheduling problem and the job-shop rescheduling problem." | |
650 | 7 | |a Applied statistics, operational research |2 sigle | |
650 | 7 | |a Mathematics |2 sigle | |
650 | 4 | |a Mathematik | |
650 | 4 | |a Genetic algorithms | |
700 | 1 | |a Ross, Peter |e Verfasser |4 aut | |
700 | 1 | |a Corne, Dave |e Verfasser |4 aut | |
810 | 2 | |a Department of Artificial Intelligence: DAI research paper |t University <Edinburgh> |v 623 |w (DE-604)BV010450646 |9 623 | |
999 | |a oai:aleph.bib-bvb.de:BVB01-006971556 |
Datensatz im Suchindex
DE-BY-TUM_call_number | 0111/2001 B 6034-623 |
---|---|
DE-BY-TUM_katkey | 664195 |
DE-BY-TUM_media_number | 040020063083 |
_version_ | 1816711722036101121 |
any_adam_object | |
author | Fang, Hsiao-Lan Ross, Peter Corne, Dave |
author_facet | Fang, Hsiao-Lan Ross, Peter Corne, Dave |
author_role | aut aut aut |
author_sort | Fang, Hsiao-Lan |
author_variant | h l f hlf p r pr d c dc |
building | Verbundindex |
bvnumber | BV010463139 |
ctrlnum | (OCoLC)32307137 (DE-599)BVBBV010463139 |
format | Book |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02031nam a2200349 cb4500</leader><controlfield tag="001">BV010463139</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">951106s1993 |||| 00||| engod</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)32307137</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV010463139</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91G</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fang, Hsiao-Lan</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems</subfield><subfield code="c">Hsiao-Lan Fang, Peter Ross, and Dave Corne</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Edinburgh</subfield><subfield code="c">1993</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">9 S.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">University <Edinburgh> / Department of Artificial Intelligence: DAI research paper</subfield><subfield code="v">623</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Abstract: "The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous efforts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderately well for the traveling salesman problem. It has the considerable merit that crossover will always produce legal schedules. A novel method for performance enhancement is examined based on dynamic sampling of the convergence rates in different parts of the genome. Our approach also promises to effectively address the open-shop scheduling problem and the job-shop rescheduling problem."</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Applied statistics, operational research</subfield><subfield code="2">sigle</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Mathematics</subfield><subfield code="2">sigle</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Genetic algorithms</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ross, Peter</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Corne, Dave</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="810" ind1="2" ind2=" "><subfield code="a">Department of Artificial Intelligence: DAI research paper</subfield><subfield code="t">University <Edinburgh></subfield><subfield code="v">623</subfield><subfield code="w">(DE-604)BV010450646</subfield><subfield code="9">623</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-006971556</subfield></datafield></record></collection> |
id | DE-604.BV010463139 |
illustrated | Not Illustrated |
indexdate | 2024-11-25T17:14:19Z |
institution | BVB |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006971556 |
oclc_num | 32307137 |
open_access_boolean | |
owner | DE-91G DE-BY-TUM |
owner_facet | DE-91G DE-BY-TUM |
physical | 9 S. |
publishDate | 1993 |
publishDateSearch | 1993 |
publishDateSort | 1993 |
record_format | marc |
series2 | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |
spellingShingle | Fang, Hsiao-Lan Ross, Peter Corne, Dave A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems Applied statistics, operational research sigle Mathematics sigle Mathematik Genetic algorithms |
title | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems |
title_auth | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems |
title_exact_search | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems |
title_full | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems Hsiao-Lan Fang, Peter Ross, and Dave Corne |
title_fullStr | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems Hsiao-Lan Fang, Peter Ross, and Dave Corne |
title_full_unstemmed | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems Hsiao-Lan Fang, Peter Ross, and Dave Corne |
title_short | A promising genetic algorithm approach to job-shop scheduling, rescheduling, and open-shop scheduling problems |
title_sort | a promising genetic algorithm approach to job shop scheduling rescheduling and open shop scheduling problems |
topic | Applied statistics, operational research sigle Mathematics sigle Mathematik Genetic algorithms |
topic_facet | Applied statistics, operational research Mathematics Mathematik Genetic algorithms |
volume_link | (DE-604)BV010450646 |
work_keys_str_mv | AT fanghsiaolan apromisinggeneticalgorithmapproachtojobshopschedulingreschedulingandopenshopschedulingproblems AT rosspeter apromisinggeneticalgorithmapproachtojobshopschedulingreschedulingandopenshopschedulingproblems AT cornedave apromisinggeneticalgorithmapproachtojobshopschedulingreschedulingandopenshopschedulingproblems |