Benchmarking Derivative-Free Global Optimization Algorithms Under Limited Dimensions and Large Evaluation Budgets

This article addresses the challenge of selecting the most suitable optimization algorithm by presenting a comprehensive computational comparison between stochastic and deterministic methods. The complexity of algorithm selection arises from the absence of a universal algorithm and the abundance of...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 29; no. 1; pp. 187 - 204
Main Authors:	Stripinis, Linas, Kudela, Jakub, Paulavicius, Remigijus
Format:	Journal Article
Language:	English
Published:	IEEE 01.02.2025
Subjects:	Benchmark testing Closed box Derivative-free global optimization deterministic algorithms Evolutionary computation evolutionary computation (EC) algorithms Linear programming nature-inspired meta-heuristics numerical benchmarking Optimization Partitioning algorithms Stochastic processes
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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