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:

DB	Citing
Scopus	1

Altmetrics: