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GECCO
2004
Springer
108views Optimization» more  GECCO 2004»
15 years 9 months ago
Simple Population Replacement Strategies for a Steady-State Multi-objective Evolutionary Algorithm
This paper explores some simple evolutionary strategies for an elitist, steady-state Pareto-based multi-objective evolutionary algorithm. The experimental framework is based on the...
Christine L. Mumford
136
Voted
GECCO
2010
Springer
176views Optimization» more  GECCO 2010»
15 years 6 months ago
A hierarchical cooperative evolutionary algorithm
To successfully search multiple coadaptive subcomponents in a solution, we developed a novel cooperative evolutionary algorithm based on a new computational multilevel selection f...
Shelly Xiaonan Wu, Wolfgang Banzhaf
CEC
2010
IEEE
14 years 7 months ago
Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison
— This paper presents Evolutionary Optimization Tool (Evoptool), an optimization toolkit that implements a set of meta-heuristics based on the Evolutionary Computation paradigm. ...
Gabriele Valentini, Luigi Malagò, Matteo Ma...
111
Voted
CEC
2007
IEEE
15 years 10 months ago
Continuous dynamic problem generators for evolutionary algorithms
— Addressing dynamic optimization problems has attracted a growing interest from the evolutionary algorithm community in recent years due to its importance in the applications of...
Renato Tinós, Shengxiang Yang
ICTAI
2005
IEEE
15 years 9 months ago
Determining the Optimal Number of Clusters Using a New Evolutionary Algorithm
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Wei Lu, Issa Traoré