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ICTAI
2009
IEEE
14 years 3 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 9 months ago
A tree-based GA representation for the portfolio optimization problem
Recently, a number of works have been done on how to use Genetic Algorithms to solve the Portfolio Optimization problem, which is an instance of the Resource Allocation problem cl...
Claus de Castro Aranha, Hitoshi Iba
OL
2010
128views more  OL 2010»
13 years 7 months ago
A biased random-key genetic algorithm for road congestion minimization
One of the main goals in transportation planning is to achieve solutions for two classical problems, the traffic assignment and toll pricing problems. The traffic assignment proble...
Luciana S. Buriol, Michael J. Hirsch, Panos M. Par...
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 1 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel
GECCO
2004
Springer
148views Optimization» more  GECCO 2004»
14 years 2 months ago
Evolving Local Search Heuristics for SAT Using Genetic Programming
Satisfiability testing (SAT) is a very active area of research today, with numerous real-world applications. We describe CLASS2.0, a genetic programming system for semi-automatica...
Alex S. Fukunaga