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Emilia Tantar

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See detailApplication of Cognitive Techniques to Network Management and Control
Kukliński, Sławomir; Wytrębowicz, Jacek; Dinh, Khoatruong et al

in Tantar, Alexandru-Adrian; Tantar, Emilia; Sun, Jian-Qiao (Eds.) et al EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (2014)

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See detailA survey on sustainability in ICT a computing perspective
Tantar, Alexandru-Adrian UL; Tantar, Emilia UL

in GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference (2014)

The rise of the data centers industry, together with the emergence of large cloud computing that require large quantities of resources to be maintained, brought the need of providing a sustainable ... [more ▼]

The rise of the data centers industry, together with the emergence of large cloud computing that require large quantities of resources to be maintained, brought the need of providing a sustainable development process. Through this paper we aim to provide an introductory insight on the status and tools available to tackle this perspective within the evolutionary and genetic algorithms community. Existing advancement are also emphasized and perspectives outlined. [less ▲]

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See detailCognition: a tool for reinforcing security in Software Defined Netwks
Tantar, Emilia UL; Palattella, Maria Rita UL; Avanesov, Tigran UL et al

in Tantar, Alexandru-Adrian; Tantar, Emilia; Jian-Qiao, Sun (Eds.) et al EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (2014)

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See detailAsymmetric quadratic landscape approximation model
Tantar, Alexandru-Adrian UL; Tantar, Emilia UL; Schütze, O.

in GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference (2014)

This work presents an asymmetric quadratic approximation model and an ε-archiving algorithm. The model allows to construct, under local convexity assumptions, descriptors for local optima points in ... [more ▼]

This work presents an asymmetric quadratic approximation model and an ε-archiving algorithm. The model allows to construct, under local convexity assumptions, descriptors for local optima points in continuous functions. A descriptor can be used to extract confidence radius information. The ε-archiving algorithm is designed to maintain and update a set of such asymmetric descriptors, spaced at some given threshold distance. An in-depth analysis is conducted on the stability and performance of the asymmetric model, comparing the results with the ones obtained by a quadratic polynomial approximation. A series of different applications are possible in areas such as dynamic and robust optimization. © 2014 ACM. [less ▲]

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See detailSpecial issue on evolutionary computing and complex systems
Bouvry, Pascal UL; Schuetze, Oliver; Coello Coello, Carlos A. et al

in SOFT COMPUTING (2013), 17(6), 909-912

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See detailOn the Foundations and the Applications of Evolutionary Computing
Del Moral, Pierre; Tantar, Alexandru-Adrian UL; Tantar, Emilia UL

in Studies in Computational Intelligence (2013), 447

Genetic type particle methods are increasingly used to sample from complex high-dimensional distributions. They have found a wide range of applications in applied probability, Bayesian statistics ... [more ▼]

Genetic type particle methods are increasingly used to sample from complex high-dimensional distributions. They have found a wide range of applications in applied probability, Bayesian statistics, information theory, and engineering sciences. Understanding rigorously these new Monte Carlo simulation tools leads to fascinating mathematics related to Feynman-Kac path integral theory and their interacting particle interpretations. In this chapter, we provide an introduction to the stochastic modeling and the theoretical analysis of these particle algorithms. We also illustrate these methods through several applications. [less ▲]

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See detailEVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation IV [EVOLVE 2013, Leiden The Netherlands, July 10-13, 2013]
Emmerich, Michael; Deutz, Andre; Schuetze, Oliver et al

Book published by Springer (2013)

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See detailEVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II
Schütze, O.; Coello, C. A. C.; Bouvry, Pascal UL et al

Book published by Springer (2012)

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See detailA classification of dynamic multi-objective optimization problems
Tantar, Alexandru-Adrian UL; Tantar, Emilia UL; Bouvry, Pascal UL

in A classification of dynamic multi-objective optimization problems (2011)

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See detailLoad balancing for sustainable ICT
Tantar, Alexandru-Adrian UL; Tantar, Emilia UL; Bouvry, Pascal UL

in Load balancing for sustainable ICT (2011)

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See detailSparse Antenna Array Optimization with the Cross-Entropy Method
Minvielle, Pierre; Tantar, Emilia UL; Tantar, Alexandru-Adrian UL et al

in IEEE Transactions on Antennas & Propagation (2011), 59(8), 2862-2871

The interest in sparse antenna arrays is growing, mainly due to cost concerns, array size limitations, etc. Formally, it can be shown that their design can be expressed as a constrained multidimensional ... [more ▼]

The interest in sparse antenna arrays is growing, mainly due to cost concerns, array size limitations, etc. Formally, it can be shown that their design can be expressed as a constrained multidimensional nonlinear optimization problem. Generally, through lack of convex property, such a multiextrema problem is very tricky to solve by usual deterministic optimization methods. In this article, a recent stochastic approach, called Cross-Entropy method, is applied to the continuous constrained design problem. The method is able to construct a random sequence of solutions which converges probabilistically to the optimal or the near-optimal solution. Roughly speaking, it performs adaptive changes to probability density functions according to the Kullback-Leibler cross-entropy. The approach efficiency is illustrated in the design of a sparse antenna array with various requirements. [less ▲]

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See detailOn dynamic multi-objective optimization - classification and performance measures
Tantar, Emilia UL; Tantar, Alexandru-Adrian UL; Bouvry, Pascal UL

in On dynamic multi-objective optimization - classification and performance measures (2011)

In this work we focus on defining how dynamism can be modeled in the context of multi-objective optimization. Based on this, we construct a component oriented classification for dynamic multi-objective ... [more ▼]

In this work we focus on defining how dynamism can be modeled in the context of multi-objective optimization. Based on this, we construct a component oriented classification for dynamic multi-objective optimization problems. For each category we provide synthetic examples that depict in a more explicit way the defined model. We do this either by positioning existing synthetic benchmarks with respect to the proposed classification or through new problem formulations. In addition, an online dynamic MNK-landscape formulation is introduced together with a new comparative metric for the online dynamic multi-objective context. [less ▲]

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See detailOn the Resilience of [distributed] Evolutionary Algorithms against Cheaters in Global Computing Platforms
Varrette, Sébastien UL; Tantar, Emilia UL; Bouvry, Pascal UL

in Proc. of the 14th Intl. Workshop on Nature Inspired Distributed Computing (NIDISC 2011), part of the 25th IEEE/ACM Intl. Parallel and Distributed Processing Symposium (IPDPS 2011) (2011)

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See detailOn the Resilience of [Distributed] EAs against Cheaters in Global Computing Platforms
Varrette, Sébastien UL; Tantar, Emilia UL; Bouvry, Pascal UL

in 25th IEEE International Symposium on Parallel and Distributed Processing (IPDPS 2011) (2011)

Detailed reference viewed: 23 (2 UL)
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See detailLandscape Analysis in Adaptive Metaheuristics for Grid Computing
Tantar, Emilia UL; Tantar, Alexandru-Adrian UL; Melab, Nouredine et al

in Parallel Programming, Models and Applications in Grid and P2P Systems (2009)

Detailed reference viewed: 26 (0 UL)