Genetic Algorithms for Selected Logistics Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F03%3A00007544" target="_blank" >RIV/60461373:22340/03:00007544 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Genetic Algorithms for Selected Logistics Problems
Original language description
The purpose of this contribution is to show that methods of AI, genetic algorithms in particular, are very efficient tools for solving problems of optimization of serial multiproduct batch plant sequencing. This work deals with the problem of finding sequence of batches that minimizes the makespan, and discusses the application of different genetic algorithms to find such optimum sequence for a flowshop topology of a batch process. This paper presents the analysis of performance of different algorithm configurations and parameter values. The results obtained using genetic algorithms are compared to those obtained using MINLP.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
CI - Industrial chemistry and chemical engineering
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
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Transport & Logistics
ISSN
1451-107X
e-ISSN
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Volume of the periodical
3
Issue of the periodical within the volume
EX
Country of publishing house
YU -
Number of pages
4
Pages from-to
152-155
UT code for WoS article
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EID of the result in the Scopus database
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