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GECCO
1999
Springer
126views Optimization» more  GECCO 1999»
15 years 8 months ago
Improving Genetic Algorithms by Search Space Reductions (with Applications to Flow Shop Scheduling)
Crossover operators that preserve common components can also preserve representation level constraints. Consequently, these constraints can be used to beneficially reduce the sea...
Stephen Y. Chen, Stephen F. Smith
PPSN
1994
Springer
15 years 8 months ago
Convergence Models of Genetic Algorithm Selection Schemes
We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes. The models predict the proportion of optimal a...
Dirk Thierens, David E. Goldberg
TKDE
2008
111views more  TKDE 2008»
15 years 3 months ago
A Point Symmetry-Based Clustering Technique for Automatic Evolution of Clusters
In this paper, a new symmetry-based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. ...
Sanghamitra Bandyopadhyay, Sriparna Saha
TEC
2002
161views more  TEC 2002»
15 years 3 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
15 years 10 months ago
GAMA (genetic algorithm driven multi-agents)for e-commerce integrative negotiation
Software agents help automate a variety of tasks including those involved in buying and selling products over the internet. The need for handling complex highly configurable produ...
Magda Bahaa Eldin Fayek, Ihab A. Talkhan, Khalil S...