Combining Lipschitz and RBF Surrogate Models for High-dimensional Computationally Expensive Problems

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU145845" target="_blank" >RIV/00216305:26210/22:PU145845 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0020025522013342" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0020025522013342</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ins.2022.11.045" target="_blank" >10.1016/j.ins.2022.11.045</a>

Result language

angličtina

Original language name

Combining Lipschitz and RBF Surrogate Models for High-dimensional Computationally Expensive Problems

Original language description

Standard evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward and computationally cheap. However, in many real-world optimization problems, these evaluations involve computationally expensive numerical simulations or physical experiments. Surrogate-assisted evolutionary algorithms (SAEAs) have recently gained increased attention for their performance in solving these types of problems. The main idea of SAEAs is the integration of an evolutionary algorithm with a selected surrogate model that approximates the computationally expensive function. In this paper, we propose a surrogate model based on a Lipschitz underestimation and use it to develop a differential evolution-based algorithm. The algorithm, called Lipschitz Surrogate-assisted Differential Evolution (LSADE), utilizes the Lipschitz-based surrogate model, along with a standard radial basis function surrogate model and a local search procedure. The experimental results on seven benchmark functions of dimensions 30, 50, 100, and 200 show that the proposed LSADE algorithm is competitive compared with the state-of-the-art algorithms under a limited computational budget, being especially effective for the very complicated benchmark functions in high dimensions.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

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

Project

<a href="/en/project/EF16_026%2F0008392" target="_blank" >EF16_026/0008392: Computer Simulations for Effective Low-Emission Energy Engineering</a><br>

Continuities

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

Publication year

2022

Confidentiality

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

Name of the periodical

INFORMATION SCIENCES

ISSN

0020-0255

e-ISSN

1872-6291

Volume of the periodical

619

Issue of the periodical within the volume

January

Country of publishing house

US - UNITED STATES

Number of pages

21

Pages from-to

457-477

UT code for WoS article

000900806500006

EID of the result in the Scopus database

2-s2.0-85142307944