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GECCO
2006
Springer
282views Optimization» more  GECCO 2006»
15 years 1 months ago
A genetic algorithm for the longest common subsequence problem
A genetic algorithm for the longest common subsequence problem encodes candidate sequences as binary strings that indicate subsequences of the shortest or first string. Its fitnes...
Brenda Hinkemeyer, Bryant A. Julstrom
GECCO
2006
Springer
189views Optimization» more  GECCO 2006»
15 years 1 months ago
Game theory as a new paradigm for phenotype characterization of genetic algorithms
In this paper, it is presented a new way to characterize the phenotype in the context of Genetic Algorithms through the use of Game Theory as a theoretical foundation to define a ...
Otávio Noura Teixeira, Artur Noura Teixeira...
GECCO
2008
Springer
250views Optimization» more  GECCO 2008»
14 years 11 months ago
Community detection in social networks with genetic algorithms
A new genetic algorithm to detect communities in social networks is presented. The algorithm uses a fitness function able to identify groups of nodes in the network having dense ...
Clara Pizzuti
FGCS
2006
82views more  FGCS 2006»
14 years 9 months ago
PGGA: A predictable and grouped genetic algorithm for job scheduling
This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimati...
Maozhen Li, Bin Yu, Man Qi
ENGL
2007
121views more  ENGL 2007»
14 years 9 months ago
A Comparison between Genetic Algorithms and Evolutionary Programming based on Cutting Stock Problem
—Genetic Algorithms (GA) and Evolutionary Programming (EP) are two well-known optimization methods that belong to the class of Evolutionary Algorithms (EA). Both methods have gen...
Raymond Chiong, Ooi Koon Beng