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GECCO
2008
Springer
112views Optimization» more  GECCO 2008»
13 years 9 months ago
Handling dynamic data structures in search based testing
There has been little attention to search based test data generation in the presence of pointer inputs and dynamic data structures, an area in which recent concolic methods have e...
Kiran Lakhotia, Mark Harman, Phil McMinn
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
13 years 9 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
GECCO
2008
Springer
117views Optimization» more  GECCO 2008»
13 years 9 months ago
Non-monotone differential evolution
The Differential Evolution algorithm uses an elitist selection, constantly pushing the population in a strict downhill search, in an attempt to guarantee the conservation of the ...
Michael G. Epitropakis, Vassilis P. Plagianakos, M...
GECCO
2008
Springer
114views Optimization» more  GECCO 2008»
13 years 9 months ago
Strategic positioning in tactical scenario planning
Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for op...
James M. Whitacre, Hussein A. Abbass, Ruhul A. Sar...
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 9 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
GECCO
2008
Springer
127views Optimization» more  GECCO 2008»
13 years 9 months ago
Social interaction in particle swarm optimization, the ranked FIPS, and adaptive multi-swarms
The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm’s success. In this study various approaches re...
Johannes Jordan, Sabine Helwig, Rolf Wanka
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 9 months 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
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 9 months ago
Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Greg Paperin
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 9 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
GECCO
2008
Springer
146views Optimization» more  GECCO 2008»
13 years 9 months ago
A formal performance modeling framework for bio-inspired ad hoc routing protocols
Bio-inspired ad hoc routing is an active area of research. The designers of these algorithms predominantly evaluate the performance of their protocols with the help of simulation ...
Muhammad Saleem, Syed Ali Khayam, Muddassar Farooq