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Ana Maria Sarmiento

Researcher at Monterrey Institute of Technology and Higher Education

Publications -  13
Citations -  107

Ana Maria Sarmiento is an academic researcher from Monterrey Institute of Technology and Higher Education. The author has contributed to research in topics: Differential evolution & Evolutionary algorithm. The author has an hindex of 6, co-authored 13 publications receiving 83 citations.

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Journal ArticleDOI

Differential evolution algorithm applied to wireless sensor distribution on different geometric shapes with area and energy optimization

TL;DR: This research applies multi-objective differential evolution algorithm to jointly optimize the sensors distribution over diverse area shapes, increase the coverage area and reduce the network energy at the same time.
Journal ArticleDOI

Routing and wavelength assignment in all optical networks using differential evolution optimization

TL;DR: The use of a novel approach based on a differential evolution (DE) algorithm to the RWA problem in wavelength-routed dense division multiplexing (DWDM) optical networks shows that the DE-RWA outperform those algorithms.
Journal ArticleDOI

Differential evolution optimization applied to the routing and spectrum allocation problem in flexgrid optical networks

TL;DR: This work introduces the application of differential evolution (DE) to the off-line RSA problem in flexible optical networks and develops two DE permutation-based algorithms named DE general approach (DE-GC) and DE relative position index (de-RPI).
Journal ArticleDOI

Differential evolution optimization applied to the wavelength converters placement problem in all optical networks

TL;DR: This paper introduces the application of Differential Evolution (DE) to the problem of the placement of wavelength converters to obtain the optimal solution and presents experiments that demonstrate the effectiveness and efficiency of the proposed evolutionary algorithm.
Proceedings ArticleDOI

Routing and spectrum allocation in flexgrid optical networks using differential evolution optimization

TL;DR: This work is the first application of a differential evolution (DE) algorithm to the RSA problem in flexible optical networks and shows that in many cases DE outperforms many other well-known evolutionary computational approaches.