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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
13 years 11 months ago
Instance similarity and the effectiveness of case injection in a genetic algorithm for binary quadratic programming
When an evolutionary algorithm addresses a sequence of instances of the same problem, it can seed its population with solutions that it found for previous instances. This techniqu...
Jason Amunrud, Bryant A. Julstrom
GECCO
2005
Springer
143views Optimization» more  GECCO 2005»
14 years 1 months ago
Advanced models of cellular genetic algorithms evaluated on SAT
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work,...
Enrique Alba, Hugo Alfonso, Bernabé Dorrons...
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
14 years 1 months ago
Genetic algorithms using low-discrepancy sequences
The random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must ...
Shuhei Kimura, Koki Matsumura
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
Collective intelligence and bush fire spotting
Bush fires cause major damage each year in many areas of the world and the earlier that they can be detected the easier it is to minimize this damage. This paper describes a coll...
David Howden, Tim Hendtlass
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
14 years 1 months ago
A Statistical Model of GA Dynamics for the OneMax Problem
A model of the dynamics of solving the counting-ones (OneMax) problem using a simple genetic algorithm (GA) is developed. It uses statistics of the early generations of GA runs to ...
Bulent Buyukbozkirli, Erik D. Goodman