Application of Genetic Algorithms to Chemical Flowshop Sequencing

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F01%3A00003855" target="_blank" >RIV/60461373:22340/01:00003855 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
Application of Genetic Algorithms to Chemical Flowshop Sequencing
Popis výsledku v původním jazyce
The purpose of this paper is to show that methods of AI, genetic algorithms in particular, are very effective at solving difficult, important real-world problems, specifically the optimization of serial multiproduct batch plant sequencing, and to presentresults of our work in this field. This work deals with the problem of finding sequence of batches that minimizes the makespan, discusses the application of different genetic algorithms to find such optimum sequence, and in addition proposes new crossover operator that offers improvement over older ones.
Název v anglickém jazyce
Application of Genetic Algorithms to Chemical Flowshop Sequencing
Popis výsledku anglicky
The purpose of this paper is to show that methods of AI, genetic algorithms in particular, are very effective at solving difficult, important real-world problems, specifically the optimization of serial multiproduct batch plant sequencing, and to presentresults of our work in this field. This work deals with the problem of finding sequence of batches that minimizes the makespan, discusses the application of different genetic algorithms to find such optimum sequence, and in addition proposes new crossover operator that offers improvement over older ones.

Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
BC - Teorie a systémy řízení
OECD FORD obor
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Rok uplatnění
2001
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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