Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy

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5th International Conference on Intelligent Systems Design and Applications (ISDA'05)

Wroclaw, Poland

September 08-September 10

ISBN: 0-7695-2286-6

	ASCII Text	x
	Mihai Oltean, Crina Grosan, Ajith Abraham, Mario Koppen, "Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy," Intelligent Systems Design and Applications, International Conference on, pp. 558-563, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005.

	BibTex	x
	@article{ 10.1109/ISDA.2005.69, author = {Mihai Oltean and Crina Grosan and Ajith Abraham and Mario Koppen}, title = {Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy}, journal ={Intelligent Systems Design and Applications, International Conference on}, volume = {0}, year = {2005}, isbn = {0-7695-2286-6}, pages = {558-563}, doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.69}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Intelligent Systems Design and Applications, International Conference on TI - Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy SN - 0-7695-2286-6 SP558 EP563 A1 - Mihai Oltean, A1 - Crina Grosan, A1 - Ajith Abraham, A1 - Mario Koppen, PY - 2005 KW - null VL - 0 JA - Intelligent Systems Design and Applications, International Conference on ER -

Mihai Oltean, Babes-Bolyai University, Romania

Crina Grosan, Babes-Bolyai University, Romania

Ajith Abraham, Chung-Ang University, S. Korea

Mario Koppen, Fraunhofer IPK Berlin, Germany

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.69

This paper proposes a novel adaptive representation for evolutionary multiobjective optimization for solving a stock modeling problem. The standard Pareto Achieved Evolution Strategy (PAES) uses real or binary representation for encoding solutions. Adaptive Pareto Archived Evolution Strategy (APAES) uses dynamic alphabets for encoding solutions. APAES is applied for modeling two popular stock indices involving 4 objective functions. Further, two bench mark test functions for multiobjective optimization are also used to illustrate the performance of the algorithm. Empirical results demonstrate APAES performs well when compared to the standard PAES.

Citation:

Mihai Oltean, Crina Grosan, Ajith Abraham, Mario Koppen, "Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy," isda, pp.558-563, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005

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