NDLI: A hybrid discrete particle swarm optimisation method for grid computation scheduling

Content Provider	IEEE Xplore Digital Library
Author	Nguyen, S.B.S. Mengjie Zhang
Copyright Year	2014
Description	Author affiliation: Evolutionary Comput. Res. Group, Victoria Univ. of Wellington, Wellington, New Zealand (Nguyen, S.B.S.; Mengjie Zhang)
Abstract	Allocating jobs to heterogeneous machines in grid systems is an important task in computational grid to effectively utilise computational resources. Particle swarm optimisation (PSO) has been recently applied to grid computation scheduling (GCS) problems and shown very promising results as compared to other meta-heuristics in the literature. However, PSO with the traditional position updating mechanism still has problem coping with the discrete nature of GCS. This paper proposed a new updating mechanism for discrete PSO that directly utilise discrete solutions from personal and global best particles. A new local search heuristic has also been proposed to refine solutions found by PSO. The results show that the hybrid PSO is more effective than other existing PSO methods in the literature when tested on two benchmark datasets. The hybrid method is also very efficient, which makes it suitable to deal with large-scale problem instances.
Starting Page	483
Ending Page	490
File Size	386016
Page Count	8
File Format	PDF
e-ISBN	9781479914883
DOI	10.1109/CEC.2014.6900658
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Matrix converters Genetic algorithms Optimization Processor scheduling Arrays Particle swarm optimization Indexes local search particle swarm optimisation grid computing scheduling
Content Type	Text
Resource Type	Article

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