Population model (evolutionary algorithm)

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Publications associées (26)

On the Analysis of Intrahost and Interhost Viral Populations: Human Cytomegalovirus as a Case Study of Pitfalls and Expectations

Jeffrey David Jensen, Sebastian Matuszewski, Susanne Petra Pfeifer

Intrahost and interhost assessments of viral diversity are often treated as measures of separate and distinct evolutionary processes, with numerous investigations reporting seemingly incompatible results between the two. For example, in human cytomegalovir ...

American Society for Microbiology2017

The Seamless Peer and Cloud Evolution Framework

Dario Floreano, Joshua Evan Auerbach, Giovanni Iacca, Guillaume Paul Olivier Leclerc

Evolutionary algorithms are increasingly being applied to problems that are too computationally expensive to run on a single personal computer due to costly fitness function evaluations and/or large numbers of fitness evaluations. Here, we introduce the Se ...

ACM Press2016

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Idan Segev, Werner Alfons Hilda Van Geit, Jean-Denis Georges Emile Courcol, Giuseppe Chindemi, Michael Emiel Gevaert

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parametrising such models to conform to the multitude of available experimental constraints is a global nonlinear optimisation problem with a comple ...

Frontiers Research Foundation2016

Design of a Passive Flow Regulator Using a Genetic Algorithm

Harald Van Lintel

Passive flow regulators are usually intended to deliver or drain a fluid at a constant rate independently from pressure variations. Microfluidic devices made of a stack of two plates are considered here: the first plate comprises a flexible silicon membran ...

Elsevier2016

Memetic Viability Evolution for Constrained Optimization

Dario Floreano, Andrea Maesani, Giovanni Iacca

The performance of evolutionary algorithms can be heavily undermined when constraints limit the feasible areas of the search space. For instance, while Covariance Matrix Adapta- tion Evolution Strategy is one of the most efficient algorithms for unconstrai ...

Institute of Electrical and Electronics Engineers2016

Design optimization of electrical hubs using hybrid evolutionary algorithm

Jean-Louis Scartezzini, Dasaraden Mauree, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik

Integration of non-dispatchable renewable energy sources such as wind and solar into the grid is challenging due to the stochastic nature of energy sources. Hence, electrical hubs (EH) and virtual power plants that combine non-dispatchable energy sources, ...

Amer Soc Mechanical Engineers2016

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