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Adaptive Genetic Algorithm with Optimized Operators for Scheduling in Computer Systems Full article

Conference Intelligent Information Processing XII
03-06 May 2024 , Shenzhen
Source Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings
Compilation, Springer. 2024. 505 c. ISBN 978-3-031-57808-3.
Journal IFIP Advances in Information and Communication Technology
ISSN: 1868-4238 , E-ISSN: 1868-422X
Output data Year: 2024, Volume: Part 1, Pages: 317-328 Pages count : 12 DOI: 10.1007/978-3-031-57808-3_23
Tags Energy, Genetic algorithm, Parallelizable job, Scheduling, Speed scaling
Authors Zakharova Yu.V. 1 , Sakhno M.Yu. 1
Affiliations
1 Sobolev Institute of Mathematics SB RAS, Omsk, Russia

Funding (1)

1 Russian Science Foundation 22-71-10015

Abstract: Modern computing and networking environments provide the important problems of efficient using such resources as energy and cores or processors. It is based on the possibility of dynamically varying the speed of processors and using parallel calculations in the execution of operations. We consider the NP-hard speed scaling scheduling problem with energy constraints and parallelizable jobs. Each job must be executed on the given number of processors. Processors can vary their speeds dynamically. It is required to assign speeds to jobs and schedule them such that the total completion time is minimized under the given energy budget. An adaptive genetic algorithm with optimized crossover operators is proposed. The optimal recombination problem is solved in the crossover operator. This problem is aimed at searching for the best possible offspring following the well-known gene transmitting property. The experimental evaluation shows that the algorithm outperforms the known metaheuristics and demonstrates the perspectives of using adaptive techniques and optimized operators.
Cite: Zakharova Y.V. , Sakhno M.Y.
Adaptive Genetic Algorithm with Optimized Operators for Scheduling in Computer Systems
In compilation Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings. – Springer., 2024. – Т.Part I. – C.317-328. – ISBN 978-3-031-57808-3. DOI: 10.1007/978-3-031-57808-3_23 Scopus OpenAlex
Dates:
Published print: Apr 6, 2024
Published online: Apr 6, 2024
Identifiers:
Scopus: 2-s2.0-85190657685
OpenAlex: W4393977319
Citing:
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