Comparing Modern Differential Evolution Variants in Multiobjective Cloud Scheduling

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10260466" target="_blank" >RIV/61989100:27240/25:10260466 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/abs/10.1145/3712255.3726659" target="_blank" >https://dl.acm.org/doi/abs/10.1145/3712255.3726659</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3712255.3726659" target="_blank" >10.1145/3712255.3726659</a>

Result language
angličtina
Original language name
Comparing Modern Differential Evolution Variants in Multiobjective Cloud Scheduling
Original language description
Cloud scheduling is a complex optimization problem balancing fast task execution for cloud users and efficient resource utilization for cloud operators. The requirements by both parties are usually limited by Service Level Agreements and Quality of Service constraints that define the level of provided service. Although many scheduling algorithms exist, the ability of nature-inspired metaheuristics to solve complex multiobjective optimization problems motivates their investigation in the context of cloud scheduling. This work evaluates the ability of modern Differential Evolution algorithm versions to schedule cloud jobs. The computational experiments are performed with a recent cloud scheduling dataset and demonstrate a large variance in the results obtained by different algorithms. Finally, is pointed out that cloud scheduling is a real-world constrained multiobjective optimization problem with a good potential to serve as a benchmark for nature-inspired metaheuristics.
Czech name
—
Czech description
—

Project
<a href="/en/project/GF22-34873K" target="_blank" >GF22-34873K: Constrained Multiobjective Optimization Based on Problem Landscape Analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion
ISBN
979-8-4007-1464-1
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
847-850
Publisher name
Association for Computing Machinery
Place of publication
New York
Event location
Malaga
Event date
Jul 14, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001564494900241

Similar results(10)