Solving the single row facility layout problem by differential evolution

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Solving the single row facility layout problem by differential evolution

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2020

Confidentiality

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

Article name in the collection

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

ISBN

978-1-4503-7128-5

ISSN

—

e-ISSN

—

Number of pages

9

Pages from-to

210-218

Publisher name

Association for Computing Machinery

Place of publication

New York

Event location

Cancún

Event date

Jul 8, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000605292300027