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Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05)
An Improved Genetic Algorithm For Multi-Objective Optimization
Dalian, China
December 05-December 08
ISBN: 0-7695-2405-2
ASCII Text
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Fu Lin, Guiming He, "An Improved Genetic Algorithm For Multi-Objective Optimization," Parallel and Distributed Computing Applications and Technologies, International Conference on, pp. 938-940, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005.
 
 
BibTex
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@article{ 10.1109/PDCAT.2005.84,
author = {Fu Lin and Guiming He},
title = {An Improved Genetic Algorithm For Multi-Objective Optimization},
journal ={Parallel and Distributed Computing Applications and Technologies, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2405-2},
pages = {938-940},
doi = {http://doi.ieeecomputersociety.org/10.1109/PDCAT.2005.84},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Parallel and Distributed Computing Applications and Technologies, International Conference on
TI - An Improved Genetic Algorithm For Multi-Objective Optimization
SN - 0-7695-2405-2
SP938
EP940
A1 - Fu Lin,
A1 - Guiming He,
PY - 2005
KW - null
VL - 0
JA - Parallel and Distributed Computing Applications and Technologies, International Conference on
ER -
 
Fu Lin, Wuhan University, Wuhan, China
Guiming He, Wuhan University, Wuhan, China
The article points out that the traditional methods for multi-objective optimization exist some drawbacks, and presents a new method for multi-objective optimization: Combining genetic search with local search. The improved genetic algorithm (IGA) introduces local search as a means of acceleration and refinement of the solutions of genetic search. The experiments show that the improved genetic algorithm (IGA), compared with the traditional genetic algorithm (GA), can improve efficiency of optimization and ensure a better convergence to the true Pareto optimal front.
Citation:
Fu Lin, Guiming He, "An Improved Genetic Algorithm For Multi-Objective Optimization," pdcat, pp.938-940, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005
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