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» On the Brittleness of Evolutionary Algorithms
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82
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BMCBI
2010
135views more  BMCBI 2010»
14 years 10 months ago
MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...
Suzanne Matthews, Tiffani L. Williams
EC
2012
289views ECommerce» more  EC 2012»
13 years 5 months ago
Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have a better knowledge about different optima...
Kalyanmoy Deb, Amit Saha
68
Voted
IWANN
2001
Springer
15 years 2 months ago
A New Approach to Evolutionary Computation: Segregative Genetic Algorithms (SEGA)
This paper looks upon the standard genetic algorithm as an artificial self-organizing process. With the purpose to provide concepts that make the algorithm more open for scalabili...
Michael Affenzeller
GECCO
2005
Springer
117views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions
To obtain the expertise to correctly perform minimally– invasive vascular interventions thorough training is required. Training using simulation systems are increasingly becomin...
Peter A. N. Bosman, Tanja Alderliesten
104
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EMO
2009
Springer
190views Optimization» more  EMO 2009»
15 years 4 months ago
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Kalyanmoy Deb, Ankur Sinha