Self-organizing Migrating Algorithm for the Single Row Facility Layout Problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246919" target="_blank" >RIV/61989100:27240/20:10246919 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9185657" target="_blank" >https://ieeexplore.ieee.org/document/9185657</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC48606.2020.9185657" target="_blank" >10.1109/CEC48606.2020.9185657</a>
Alternative languages
Result language
angličtina
Original language name
Self-organizing Migrating Algorithm for the Single Row Facility Layout Problem
Original language description
Single row facility layout problem is an important problem encountered in facility design, factory construction, production optimization, and other areas. At the same time, it is a challenging NP-hard combinatorial optimization problem that has been addressed by many advanced algorithms. In practical scenarios, real-world problems can be cast as single row facility location problem instances with different high-level properties and efficient algorithms that can solve them are sought. This work uses a variant of the self-organizing migration algorithm developed recently for permutation problems to tackle the single row facility layout problem and evaluates its accuracy and performance. (C) 2020 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LTAIN19176" target="_blank" >LTAIN19176: Metaheuristics Framework for Multi-objective Combinatorial Optimization Problems (META MO-COP)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
ISBN
978-1-72816-929-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Glasgow
Event date
Jul 19, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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