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GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 8 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 11 months ago
Ensemble selection for evolutionary learning using information theory and price's theorem
This paper presents an information theoretic perspective on design and analysis of evolutionary algorithms. Indicators of solution quality are developed and applied not only to in...
Stuart W. Card, Chilukuri K. Mohan
EC
2011
240views ECommerce» more  EC 2011»
13 years 2 months ago
HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization
Abstract—In the field of evolutionary multi-criterion optimization, the hypervolume indicator is the only single set quality measure that is known to be strictly monotonic with ...
Johannes Bader, Eckart Zitzler
GECCO
2009
Springer
115views Optimization» more  GECCO 2009»
14 years 1 days ago
Rapid prototyping using evolutionary approaches: part 2
In this paper we extend the work done in [5], where authors have proposed a evolutionary multi-objective approach to Rapid Prototyping (RP), to decipher optimal build orientation ...
Nikhil Padhye, Subodh Kalia
CEC
2007
IEEE
14 years 1 months ago
Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
Dimo Brockhoff, Eckart Zitzler