| Evolutionary
Multiobjective Optimization: Papers
An
Efficient Approach to Unbounded Bi-Objective Archives – Introducing
the Mak_ Tree Algorithm
(Page 619)
A. Berry (University of Tasmania)
P. Vamplew (University of Ballarat)
Combining
Gradient Techniques for Numerical Multi–Objective Evolutionary Optimization
(Page 627)
P. A. N. Bosman (Centre for Mathematics and Computer
Science)
E. D. de Jong (Utrecht University)
Reference
Point Based Multi-Objective Optimization Using Evolutionary Algorithms
(Page 635)
K. Deb, J. Sundar (Indian Institute of Technology)
Towards
Estimating Nadir Objective Vector Using Evolutionary Approaches
(Page 643)
K. Deb, S. Chaudhuri (Indian Institute of Technology)
K. Meittinen (Helsinki School of Economics)
On
The Effect of Populations in Evolutionary Multi-objective Optimization
(Page 651)
O. Giel (Universität Dortmund)
P. K. Lehre (Norwegian University of Science and Technology)
Local
Search for Multiobjective Function Optimization: Pareto Descent Method
(Page 659)
K. Harada, J. Sakuma, S. Kobayashi (Tokyo Institute
of Technology)
Hybridization
of Genetic Algorithm and Local Search in Multiobjective Function Optimization:
Recommendation of GA then LS
(Page 667)
K. Harada (Tokyo Institute of Technology)
K. Ikeda (Kyoto University)
S. Kobayashi, J. Sakuma, I. Ono (Tokyo Institute of
Technology)
A
New Proposal for Multi-Objective Optimzation using Differential Evolution
and Rough Sets Theory
(Page 675)
A. G. Hernández-Díaz (Pablo de Olavide University)
L. V. Santana-Quintero (CINVESTAV-IPN)
C. Coello Coello (CINVESTAV-IPN)
R. Caballero (University of Málaga)
J. Molina (University of Málaga)
Rotated
Test Problems for Assessing the Performance of Multi-objective Optimization
Algorithms
(Page 683)
A. W. Iorio (RMIT University)
X. Li (RMIT University)
Incorporating
Directional Information within a Differential Evolution Algorithm for
Multi-objective Optimization
(Page 691)
A. W. Iorio, X. Li (RMIT University)
Mulitobjective
Genetic Algorithms for Materialized View Selection in OLAP Data Warehouses
(Page 699)
M. Lawrence (Dalhousie University)
Inside
a Predator-Prey Model for Multi-Objective Optimization: A Second Study
(Page 707)
C. Grimme, K. Schmitt (University of Dortmund)
An
Efficient Multi-objective Evolutionary Algorithm with Steady-State Replacement
Model (Page 715)
D. Srinivasan, L. Rachmawati (National University
of Singapore)
Multi-objective
Evolutionay Optimization for Visual Data Mining with Virtual Reality
Spaces: Application to Alzheimer Gene Expressions
(Page 723)
J. J. Valdés, A. J. Barton (National Research Council
Canada)
Design
Synthesis of Microelectromechanical Systems Using Genetic Algorithms
with Component-Based Genotype Representation
(Page 731)
Y. Zhang (University of California at Berkeley)
R. Kamalian (Kyushu University)
A. M. Agogino, C. H. Séquin (University of California
at Berkeley)
Evolutionary
Multiobjective Optimization: Posters
Incorporation
of Decision Maker's Preference into Evolutionary Multiobjective Optimization
Algorithms (Page 741)
H. Ishibuchi, Y. Nojima, K. Narukawa, T. Doi (Osaka
Prefecture University)
The
Multi-Objective Constrained Assignment Problem
(Page 743)
M. P. Kleeman, G. B. Lamont (Air Force Institute of
Technology)
A
New Multi-Objective Evolutionary Algorithm for Solving High Complex
Multi-Objective Problems (Page
745)
K. Li (Jiangxi University of Science and Technology,
Jiangxi Norman University, Wuhan University)
X. Yue (Jiangxi University of Science and Technology)
L. Kang (Wuhan University)
Z. Chen (Southern Methodist University)
Comparison
of Multi-Objective Evolutionary Algorithms in Optimizing Combinations
of Reinsurance Contracts (Page
747)
I. Oesterreicher, A. Mitschele (University Karlsruhe)
F. Schlottmann (GILLARDON AG)
D. Seese (University Karlsruhe)
A
Multi-objective Evolutionary Algorithm with Weighted-Sum Niching for
Convergence on Knee Regions
(Page 749)
L. Rachmawati, D. Srinivasan (National University
of Singapore)
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