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» An Indirect Genetic Algorithm for Set Covering Problems
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96
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PR
1998
86views more  PR 1998»
14 years 10 months ago
Optimizing the cost matrix for approximate string matching using genetic algorithms
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
Marc Parizeau, Nadia Ghazzali, Jean-Françoi...
88
Voted
GECCO
2010
Springer
212views Optimization» more  GECCO 2010»
15 years 3 months ago
Generative and developmental systems
This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
Kenneth O. Stanley
89
Voted
GECCO
2009
Springer
152views Optimization» more  GECCO 2009»
15 years 3 months ago
A data-based coding of candidate strings in the closest string problem
Given a set of strings S of equal lengths over an alphabet Σ, the closest string problem seeks a string over Σ whose maximum Hamming distance to any of the given strings is as s...
Bryant A. Julstrom
86
Voted
GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
15 years 4 months ago
Hybrid multiobjective genetic algorithm with a new adaptive local search process
This paper is concerned with a specific brand of evolutionary algorithms: Memetic algorithms. A new local search technique with an adaptive neighborhood setting process is introdu...
Salem F. Adra, Ian Griffin, Peter J. Fleming
78
Voted
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 5 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna