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GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
15 years 7 months ago
Solving constrained multi-objective problems by objective space analysis
In this paper a new approach to solve constrained multi-objective problems by way of evolutionary multi-objective optimization is introduced. In contrast to former evolutionary ap...
Gideon Avigad, Carlos A. Coello Coello
IJDMB
2010
61views more  IJDMB 2010»
15 years 5 months ago
On a novel coalescent model for genome-wide evolution of Copy Number Variations
: Since we are limited in our knowledge of human demographic history and variations of recombination and mutation rates, large-scale computer simulation is a necessary tool in gene...
Antonina Mitrofanova, Bhubaneswar (Bud) Mishra
IEEECIT
2009
IEEE
16 years 1 months ago
Clustering of Software Systems Using New Hybrid Algorithms
—Software clustering is a method for increasing software system understanding and maintenance. Software designers, first use MDG graph to model the structure of software system. ...
Ali Safari Mamaghani, Mohammad Reza Meybodi
185
Voted
AAAI
2006
15 years 8 months ago
Representing Systems with Hidden State
We discuss the problem of finding a good state representation in stochastic systems with observations. We develop a duality theory that generalizes existing work in predictive sta...
Christopher Hundt, Prakash Panangaden, Joelle Pine...
AEI
2005
99views more  AEI 2005»
15 years 6 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson