Multiobjective evolutionary algorithms for energy and service level scheduling in a federation of distributed datacenters

DOI10.1111/itor.12294zbMath1358.90124OpenAlexW2576119772WikidataQ57605782 ScholiaQ57605782MaRDI QIDQ2968499

S. Nesmachnow, Bernabé Dorronsoro, Santiago Iturriaga

Publication date: 16 March 2017

Published in: International Transactions in Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/itor.12294

zbMATH Keywords

optimizationschedulingparallel computingenergy sector

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• SPEA2
• MOCell

Cites Work

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• Some observations on optimal frequency selection in DVFS-based energy consumption minimization
• Cellular genetic algorithms
• MOCell: A cellular genetic algorithm for multiobjective optimization
• Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
• Evolutionary Algorithms for Mobile Ad Hoc Networks
• A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems