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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
10 years 9 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
10 years 9 months ago
Integrating real-time analysis with the dendritic cell algorithm through segmentation
As an immune inspired algorithm, the Dendritic Cell Algorithm (DCA) has been applied to a range of problems, particularly in the area of intrusion detection. Ideally, the intrusio...
Feng Gu, Julie Greensmith, Uwe Aickelin
GECCO
2009
Springer
10 years 9 months ago
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
In this paper, we rigorously analyse how the magnitude and frequency of change may affect the performance of the algorithm (1+1) EAdyn on a set of artificially designed pseudo-Bo...
Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
10 years 9 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
GECCO
2009
Springer
143views Optimization» more  GECCO 2009»
10 years 9 months ago
Exploiting hierarchical clustering for finding bounded diameter minimum spanning trees on euclidean instances
The bounded diameter minimum spanning tree problem is an NP-hard combinatorial optimization problem arising, for example, in network design when quality of service is of concern. ...
Martin Gruber, Günther R. Raidl
GECCO
2009
Springer
141views Optimization» more  GECCO 2009»
10 years 9 months ago
Visualizing the search process of particle swarm optimization
It is a hard problem to understand the search process of particle swarm optimization over high-dimensional domain. The visualization depicts the total search process and then it w...
Yong-Hyuk Kim, Kang Hoon Lee, Yourim Yoon
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
10 years 9 months ago
Crossover operators for multiobjective k-subset selection
Genetic algorithms are often applied to combinatorial optimization problems, the most popular one probably being the traveling salesperson problem. In contrast to permutations use...
Thorsten Meinl, Michael R. Berthold
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
10 years 9 months ago
Insight knowledge in search based software testing
Software testing can be re-formulated as a search problem, hence search algorithms (e.g., Genetic Algorithms) can be used to tackle it. Most of the research so far has been of emp...
Andrea Arcuri
GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
10 years 9 months ago
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Gabriela Ochoa, Rong Qu, Edmund K. Burke
GECCO
2009
Springer
166views Optimization» more  GECCO 2009»
10 years 9 months ago
Genetic programming in the wild: evolving unrestricted bytecode
We describe a methodology for evolving Java bytecode, enabling the evolution of extant, unrestricted Java programs, or programs in other languages that compile to Java bytecode. B...
Michael Orlov, Moshe Sipper
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