Proceedings of the 2nd International Conference on Science and Social Research (ICSSR 2013)

A DEA-GA multi-objective scheduling algorithm for Chip-Multiprocessor

Authors
Song Chai, Yubai Li, Chang Wu, Jian Wang
Corresponding Author
Song Chai
Available Online July 2013.
DOI
https://doi.org/10.2991/icssr-13.2013.153How to use a DOI?
Keywords
DEA; efficiency; Genetic Algorithm; multi-objective; scheduling; Chip Multiprocessor.
Abstract
In this paper, a Data Envelopment analysis based Genetic Algorithm (DEA-GA) is proposed for multi-objective scheduling on Chip-Multiprocessor. The proposal adopts modified GA as the searching heuristic to explore the solution space, and the fitness of each individual (schedule) is evaluated using the DEA approach. Three of the schedule metrics, namely makespan, energy and load balance are used to construct the multi-input multi-output Decision Making Units in the DEA, and the BCC super efficiency of each schedule is calculated. In the modified genetic algorithm, the metapopulation is divided into three subpopulations each optimizing a single metric. The top performance individuals in each subpopulation are then regrouped and applied DEA evaluation. Comparing to other multi-objective scheduling algorithm in simulations, our proposal always produces more efficient schedule solutions.
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Proceedings
2nd International Conference on Science and Social Research (ICSSR 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2013
ISBN
978-90-78677-75-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icssr-13.2013.153How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Song Chai
AU  - Yubai Li
AU  - Chang Wu
AU  - Jian Wang
PY  - 2013/07
DA  - 2013/07
TI  - A DEA-GA multi-objective scheduling algorithm for Chip-Multiprocessor
BT  - 2nd International Conference on Science and Social Research (ICSSR 2013)
PB  - Atlantis Press
SP  - 661
EP  - 665
SN  - 1951-6851
UR  - https://doi.org/10.2991/icssr-13.2013.153
DO  - https://doi.org/10.2991/icssr-13.2013.153
ID  - Chai2013/07
ER  -