A Hybrid Many-Objective Optimization Algorithm for Job Scheduling in Cloud Computing Based on Merge-and-Split Theory

A Hybrid Many-Objective Optimization Algorithm for Job Scheduling in Cloud Computing Based on Merge-and-Split Theory

Scheduling jobs within a cloud environment is a critical area of research that necessitates meticulous analysis. It entails the challenge of optimally assigning jobs to various cloud servers, each with different capabilities, and is classified as a non-deterministic polynomial (NP) problem. Many con...

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Bibliographic Details
Main Authors: Mustafa Ibrahim Khaleel, Mejdl Safran, Sultan Alfarhood, Michelle Zhu
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Mathematics
Subjects:
mean grey wolf optimization
cloud computing
job scheduling
improved sunflower algorithm
merge-and-split cooperative game theory
Online Access:https://www.mdpi.com/2227-7390/11/16/3563

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https://www.mdpi.com/2227-7390/11/16/3563

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