Scheduling Job Shops Using Genetic Algorithms and Local Search Framework
Result description
This paper provides a comparison of the application of stochastic heuristic techniques (genetic algorithms, simulated annealing and tabu search) to job shop scheduling. It presents computational results achieved for three typical representation schemes using standard benchmark problems.
Keywords
Job shop schedulingstochastic heuristic methodsdisjunctive graph
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Scheduling Job Shops Using Genetic Algorithms and Local Search Framework
Original language description
This paper provides a comparison of the application of stochastic heuristic techniques (genetic algorithms, simulated annealing and tabu search) to job shop scheduling. It presents computational results achieved for three typical representation schemes using standard benchmark problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
1999
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mendel '99. 5th International Conference on Soft Computing
ISBN
80-214-1131-7
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
VUT FSI ÚAI
Place of publication
Brno, ČR
Event location
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Event date
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Type of event by nationality
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UT code for WoS article
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Basic information
Result type
D - Article in proceedings
CEP
BB - Applied statistics, operational research
Year of implementation
1999