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Fourth International Conference on Hybrid Intelligent Systems (HIS'04)
Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems
Kitakyushu, Japan
December 05-December 08
ISBN: 0-7695-2291-2
ASCII Text
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Laetitia Jourdan, David Corne, Dragan Savic, Godfrey Walters, "Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems," Hybrid Intelligent Systems, International Conference on, pp. 434-439, Fourth International Conference on Hybrid Intelligent Systems (HIS'04), 2004.
 
 
BibTex
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@article{ 10.1109/ICHIS.2004.58,
author = {Laetitia Jourdan and David Corne and Dragan Savic and Godfrey Walters},
title = {Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems},
journal ={Hybrid Intelligent Systems, International Conference on},
volume = {0},
year = {2004},
isbn = {0-7695-2291-2},
pages = {434-439},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICHIS.2004.58},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Hybrid Intelligent Systems, International Conference on
TI - Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems
SN - 0-7695-2291-2
SP434
EP439
A1 - Laetitia Jourdan,
A1 - David Corne,
A1 - Dragan Savic,
A1 - Godfrey Walters,
PY - 2004
KW - null
VL - 0
JA - Hybrid Intelligent Systems, International Conference on
ER -
 
Laetitia Jourdan, University of Exeter, UK
David Corne, University of Exeter, UK
Dragan Savic, University of Exeter, UK
Godfrey Walters, University of Exeter, UK
In this article, we present our latest work with a hybrid multiobjective evolutionary algorithm called LEMMO (Learnable Evolution Model for Multi-Objective Optimization) which integrates machine learning into evolutionary search based on Michalski's "LEM" approach. The objective is to both improve the performance of the MOEA and to reduce the number of evaluations needed when used for optimising the design of water distribution networks (where evaluations are highly computationally costly). We compare LEMMO with NSGA-II and conclude that our approach is very promising for improved speed and quality in the water systems optimisation domain.
Citation:
Laetitia Jourdan, David Corne, Dragan Savic, Godfrey Walters, "Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems," his, pp.434-439, Fourth International Conference on Hybrid Intelligent Systems (HIS'04), 2004
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