Parallel Function Optimisation Using Evolutionary Algorithms and Deterministic Neighbourhood Search

Zgeras, Ioannis; Brehm, Jürgen; Reisch, Andreas

Author:

Abstract

Modern computer hardware provides massive computational power by parallelism. However, many of the existing algorithms and frameworks are optimised for sequential execution and are not capable to be parallelised or do not scale well on complex parallel architectures. In our paper, we present a metaheuristic consisting of a parallel Evolutionary Algorithm and a parallel Neighbourhood Search. For the implementation massively parallel GPUs are used. This framework is evaluated on the application of function optimisation.

Citation
BibTeX

Zgeras, I., Brehm, J. & Reisch, A., (2011). Parallel Function Optimisation Using Evolutionary Algorithms and Deterministic Neighbourhood Search. PARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware: Vol. 28, No. 1. Gesellschaft für Informatik e.V.. (S. 152-156). DOI: 10.1007/BF03341994

@article{mci/Zgeras2011,
author = {Zgeras, Ioannis AND Brehm, Jürgen AND Reisch, Andreas},
title = {Parallel Function Optimisation Using Evolutionary Algorithms and Deterministic Neighbourhood Search},
journal = {PARS},
volume = {},
number = {28, No. 1},
year = {2011},
,
pages = { 152-156 } ,
doi = { 10.1007/BF03341994 }
}

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