Markov Chain Analysis of Evolution Strategies on a Linear Constraint Optimization Problem

This paper analyses a $(1,\lambda)$-Evolution Strategy, a randomised comparison-based adaptive search algorithm, on a simple constraint optimisation problem. The algorithm uses resampling to handle the constraint and optimizes a linear function with a linear constraint. Two cases are investigated: first the case where the step-size is constant, and second the case where the step-size is adapted using path length control. We exhibit for each case a Markov chain whose stability analysis would allow us to deduce the divergence of the algorithm depending on its internal parameters. We show divergence at a constant rate when the step-size is constant. We sketch that with step-size adaptation geometric divergence takes place. Our results complement previous studies where stability was assumed.Comment: Amir Hussain; Zhigang Zeng; Nian Zhang. IEEE Congress on Evolutionary Computation, Jul 2014, Beijing, Chin

Markov Chain Analysis of Cumulative Step-size Adaptation on a Linear Constrained Problem

This paper analyzes a (1, $\lambda$)-Evolution Strategy, a randomized comparison-based adaptive search algorithm, optimizing a linear function with a linear constraint. The algorithm uses resampling to handle the constraint. Two cases are investigated: first the case where the step-size is constant, and second the case where the step-size is adapted using cumulative step-size adaptation. We exhibit for each case a Markov chain describing the behaviour of the algorithm. Stability of the chain implies, by applying a law of large numbers, either convergence or divergence of the algorithm. Divergence is the desired behaviour. In the constant step-size case, we show stability of the Markov chain and prove the divergence of the algorithm. In the cumulative step-size adaptation case, we prove stability of the Markov chain in the simplified case where the cumulation parameter equals 1, and discuss steps to obtain similar results for the full (default) algorithm where the cumulation parameter is smaller than 1. The stability of the Markov chain allows us to deduce geometric divergence or convergence , depending on the dimension, constraint angle, population size and damping parameter, at a rate that we estimate. Our results complement previous studies where stability was assumed.Comment: Evolutionary Computation, Massachusetts Institute of Technology Press (MIT Press): STM Titles, 201

Development and mechanical characterization of porous titanium bone substitutes

The authors wish to thank Dr J.-M. Hiver from Institut Jean Lamour, Ecole des Mines de Nancy for his participation in the computed tomography analysis of the porous samplesCommercially Pure Porous Titanium (CPPTi) can be used for surgical implants to avoid the stress shielding effect due to the mismatch between the mechanical properties of titanium and bone. Most researchers in this area deal with randomly distributed pores or simple architectures in titanium alloys. The control of porosity, pore size and distribution is necessary to obtain implants with mechanical properties close to those of bone and to ensure their osseointegration. The aim of the present work was therefore to develop and characterize such a specific porous structure. First of all, the properties of titanium made by Selective Laser Melting (SLM) were characterized through experimental testing on bulk specimens. An elementary pattern of the porous structure was then designed to mimic the orthotropic properties of the human bone following several mechanical and geometrical criteria. Finite Element Analysis (FEA) was used to optimize the pattern. A porosity of 53% and pore sizes in the range of 860 to 1500 μm were finally adopted. Tensile tests on porous samples were then carried out to validate the properties obtained numerically and identif the failure modes of the samples. Finally, FE elastoplastic analyses were performed on the porous samples in order to propose a failure criterion for the design of porous substitutes

Gestion Financière des Fondations et Fonds de Dotations : Enquête 2018

The purpose of this survey is to learn about the financial management practices of foundations and funds in France.A first edition of this study was published in 2011 and a second in 2014.It was carried out at the initiative of the French Center of Funds and Foundations in partnership with Amadeis.Opinions were collected during the summer of 2018 by means of a questionnaire.

Using a virtual cortical module implementing a neural field model to modulate brain rhythms in Parkinson’s disease

We propose a new method for selective modulation of cortical rhythms based on neural field theory, in which the activity of a cortical area is extensively monitored using a two-dimensional microelectrode array. The example of Parkinson’s disease illustrates the proposed method, in which a neural field model is assumed to accurately describe experimentally recorded activity. In addition, we propose a new closed-loop stimulation signal that is both space- and time- dependent. This method is especially designed to specifically modulate a targeted brain rhythm, without interfering with other rhythms. A new class of neuroprosthetic devices is also proposed, in which the multielectrode array is seen as an artificial neural network interacting with biological tissue. Such a bio-inspired approach may provide a solution to optimize interactions between the stimulation device and the cortex aiming to attenuate or augment specific cortical rhythms. The next step will be to validate this new approach experimentally in patients with Parkinson’s disease