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» Evolutionary algorithms and matroid optimization problems
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IJHIS
2006
94views more  IJHIS 2006»
13 years 8 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
13 years 9 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
TEC
2002
128views more  TEC 2002»
13 years 7 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
COR
2010
110views more  COR 2010»
13 years 8 months ago
An evolutionary method for complex-process optimization
In this paper we present a new evolutionary method for complex-process optimization. It is partially based on principles of the scatter search methodology, but it makes use of inn...
Jose A. Egea, Rafael Martí, Julio R. Banga
ICML
2003
IEEE
14 years 1 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens