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GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
15 years 3 months ago
Designing safe, profitable automated stock trading agents using evolutionary algorithms
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...
Harish Subramanian, Subramanian Ramamoorthy, Peter...
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
15 years 26 days ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
FOGA
2011
14 years 3 months ago
Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics
Analyzing the computational complexity of evolutionary algorithms (EAs) for binary search spaces has significantly informed our understanding of EAs in general. With this paper, ...
Greg Durrett, Frank Neumann, Una-May O'Reilly
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 5 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2007
Springer
153views Optimization» more  GECCO 2007»
15 years 6 months ago
Parallel genetic algorithm: assessment of performance in multidimensional scaling
Visualization of multidimensional data by means of Multidimensional Scaling (MDS) is a popular technique of exploratory data analysis widely usable, e.g. in analysis of bio-medica...
Antanas Zilinskas, Julius Zilinskas