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» On the Brittleness of Evolutionary Algorithms
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BIBE
2008
IEEE
15 years 4 months ago
Robust parameter identification for biological circuit calibration
Abstract-The aim of this work is to compare some deterministic optimization algorithms and evolutionary algorithms on parameter estimation in a biological circuit design problem: t...
Giuseppe Nicosia, Eva Sciacca
TEC
2008
98views more  TEC 2008»
14 years 10 months ago
Opposition-Based Differential Evolution
Evolutionary Algorithms (EAs) are well-known optimization approaches to cope with non-linear, complex problems. These population-based algorithms, however, suffer from a general we...
Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M. A...
CEC
2009
IEEE
15 years 4 months ago
What is situated evolution?
—In this paper we discuss the notion of situated evolution. Our treatment includes positioning situated evolution on the map of evolutionary processes in terms of time- and space...
Martijn C. Schut, Evert Haasdijk, A. E. Eiben
EC
2000
187views ECommerce» more  EC 2000»
14 years 9 months ago
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function i...
Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
15 years 3 months ago
Using evolutionary algorithms for the unit testing of object-oriented software
As the paradigm of object orientation becomes more and more important for modern IT development projects, the demand for an automated test case generation to dynamically test obje...
Stefan Wappler, Frank Lammermann