Novel Random Key Encoding Schemes for the Differential Evolution of Permutation Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10249025" target="_blank" >RIV/61989100:27240/22:10249025 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9449662" target="_blank" >https://ieeexplore.ieee.org/document/9449662</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TEVC.2021.3087802" target="_blank" >10.1109/TEVC.2021.3087802</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Novel Random Key Encoding Schemes for the Differential Evolution of Permutation Problems

Popis výsledku v původním jazyce

Differential evolution is a powerful nature-inspired real-parameter optimization algorithm that has been successfully used to solve a number of hard optimization problems. It has been used to tackle both continuous and discrete optimization problems. The application of a continuous method to discrete problems involves several challenges, including solution representation and search space-solution space mapping. In this work, we study random key encoding, a popular encoding scheme that is used to represent permutations in high-dimensional continuous spaces. We analyze the search space it constitutes, study its structure and properties, and introduce two novel modifications of the encoding. We investigate the proposed encoding strategies in the context of four variants of the differential evolution algorithm and demonstrate their usefulness for two widespread permutation problems: 1) the linear ordering problem and 2) the traveling salesman problem.

Název v anglickém jazyce

Novel Random Key Encoding Schemes for the Differential Evolution of Permutation Problems

Popis výsledku anglicky

Differential evolution is a powerful nature-inspired real-parameter optimization algorithm that has been successfully used to solve a number of hard optimization problems. It has been used to tackle both continuous and discrete optimization problems. The application of a continuous method to discrete problems involves several challenges, including solution representation and search space-solution space mapping. In this work, we study random key encoding, a popular encoding scheme that is used to represent permutations in high-dimensional continuous spaces. We analyze the search space it constitutes, study its structure and properties, and introduce two novel modifications of the encoding. We investigate the proposed encoding strategies in the context of four variants of the differential evolution algorithm and demonstrate their usefulness for two widespread permutation problems: 1) the linear ordering problem and 2) the traveling salesman problem.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/LTAIN19176" target="_blank" >LTAIN19176: Metaheuristický rámec pro vícecílové kombinatorické optimalizační problémy (META MO-COP)</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Evolutionary Computation

ISSN

1089-778X

e-ISSN

1941-0026

Svazek periodika

26

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

43-57

Kód UT WoS článku

000748370700008

EID výsledku v databázi Scopus

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