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GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 8 months ago
Accelerating convergence using rough sets theory for multi-objective optimization problems
We propose the use of rough sets theory to improve the first approximation provided by a multi-objective evolutionary algorithm and retain the nondominated solutions using a new ...
Luis V. Santana-Quintero, Carlos A. Coello Coello
ESWA
2006
114views more  ESWA 2006»
13 years 7 months ago
Bankruptcy prediction with neural logic networks by means of grammar-guided genetic programming
The paper demonstrates the efficient use of hybrid intelligent systems for solving the classification problem of bankruptcy. The aim of the study is to obtain classification schem...
Athanasios Tsakonas, Georgios Dounias, Michael Dou...
CEC
2007
IEEE
13 years 11 months ago
Development and validation of different hybridization strategies between GA and PSO
In this paper a new class of hybridization strategies between GA and PSO is presented and validated. The Genetical Swarm Optimization (GSO) approach is presented here with respect ...
A. Gandelli, F. Grimaccia, Marco Mussetta, Paola P...
GECCO
2004
Springer
112views Optimization» more  GECCO 2004»
14 years 1 months ago
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...
Hisao Ishibuchi, Kaname Narukawa
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolutionary testing of state-based programs
The application of Evolutionary Algorithms to structural test data generation, known as Evolutionary Testing, has to date largely focused on programs with input-output behavior. H...
Phil McMinn, Mike Holcombe