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GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
14 years 10 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck
WOSP
2010
ACM
14 years 9 months ago
Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms
Quantitative prediction of quality properties (i.e. extrafunctional properties such as performance, reliability, and cost) of software architectures during design supports a syste...
Anne Martens, Heiko Koziolek, Steffen Becker, Ralf...
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 1 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
PR
2008
131views more  PR 2008»
14 years 9 months ago
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Salvador García, José Ramón C...
CEC
2007
IEEE
14 years 9 months ago
Designing memetic algorithms for real-world applications using self-imposed constraints
— Memetic algorithms (MAs) combine the global exploration abilities of evolutionary algorithms with a local search to further improve the solutions. While a neighborhood can be e...
Thomas Michelitsch, Tobias Wagner, Dirk Biermann, ...