Solving the single row facility layout problem by differential evolution

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246554" target="_blank" >RIV/61989100:27240/20:10246554 - isvavai.cz</a>

Výsledek na webu

<a href="https://dl.acm.org/doi/abs/10.1145/3377930.3389839" target="_blank" >https://dl.acm.org/doi/abs/10.1145/3377930.3389839</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3377930.3389839" target="_blank" >10.1145/3377930.3389839</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Solving the single row facility layout problem by differential evolution

Popis výsledku v původním jazyce

Differential evolution is an efficient evolutionary optimization paradigm that has shown a good ability to solve a variety of practical problems, including combinatorial optimization ones. Single row facility layout problem is an NP-hard permutation problem often found in facility design, factory construction, production optimization, and other areas. Real-world problems can be cast as large single row facility location problem instances with different high-level properties and efficient algorithms that can solve them efficiently are needed. In this work, the differential evolution is used to solve the single row facility location problem and the ability of three different variants of the algorithm to evolve solutions to various problem instances is studied. (C) 2020 ACM.

Název v anglickém jazyce

Solving the single row facility layout problem by differential evolution

Popis výsledku anglicky

Differential evolution is an efficient evolutionary optimization paradigm that has shown a good ability to solve a variety of practical problems, including combinatorial optimization ones. Single row facility layout problem is an NP-hard permutation problem often found in facility design, factory construction, production optimization, and other areas. Real-world problems can be cast as large single row facility location problem instances with different high-level properties and efficient algorithms that can solve them efficiently are needed. In this work, the differential evolution is used to solve the single row facility location problem and the ability of three different variants of the algorithm to evolve solutions to various problem instances is studied. (C) 2020 ACM.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference

ISBN

978-1-4503-7128-5

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

210-218

Název nakladatele

Association for Computing Machinery

Místo vydání

New York

Místo konání akce

Cancún

Datum konání akce

8. 7. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000605292300027