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» Solving Hierarchical Optimization Problems Using MOEAs
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GECCO
2008
Springer
153views Optimization» more  GECCO 2008»
15 years 4 months ago
G-Metric: an M-ary quality indicator for the evaluation of non-dominated sets
An open problem in multiobjective optimization using the Pareto optimality criteria, is how to evaluate the performance of different evolutionary algorithms that solve multi– o...
Giovanni Lizárraga Lizárraga, Arturo...
124
Voted
GECCO
2008
Springer
161views Optimization» more  GECCO 2008»
15 years 4 months ago
A new quantum behaved particle swarm optimization
This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the cha...
Millie Pant, Radha Thangaraj, Ajith Abraham
AAAI
1998
15 years 4 months ago
Finding Optimal Strategies for Imperfect Information Games
Weexaminethree heuristic algorithms for gameswith imperfect information: Monte-carlo sampling, and two newalgorithms wecall vector minimaxingand payoffreduction minimaxing. Wecomp...
Ian Frank, David A. Basin, Hitoshi Matsubara
131
Voted
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
15 years 9 months ago
Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression
We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. B...
Shirish Krishnaj Shevade, Wei Chu
106
Voted
GECCO
2008
Springer
112views Optimization» more  GECCO 2008»
15 years 4 months ago
Parameter-less evolutionary search
The paper presents the parameter-less implementation of an evolutionary-based search. It does not need any predefined control parameters values, which are usually used for geneti...
Gregor Papa