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Pablo Moscato

Researcher at University of Newcastle

Publications -  208
Citations -  10204

Pablo Moscato is an academic researcher from University of Newcastle. The author has contributed to research in topics: Memetic algorithm & Evolutionary algorithm. The author has an hindex of 39, co-authored 203 publications receiving 9582 citations. Previous affiliations of Pablo Moscato include Karlsruhe Institute of Technology & Edith Cowan University.

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On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms

Pablo Moscato
TL;DR: In this paper, the authors present a short abstract, which is a summary of the paper.Short abstract, isn't it? But it is short abstracts, not abstracts.
Book

New Ideas In Optimization

TL;DR: The techniques treated in this text represent research as elucidated by the leaders in the field and are applied to real problems, such as hilllclimbing, simulated annealing, and tabu search.
Journal ArticleDOI

Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20

TL;DR: To identify multiple sclerosis (MS) susceptibility loci, a genome-wide association study in 1,618 cases and used shared data for 3,413 controls and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15.
Book ChapterDOI

A Gentle Introduction to Memetic Algorithms

TL;DR: The generic denomination of ‘Memetic Algorithms’ (MAs) is used to encompass a broad class of metaheuristics (i.e. general purpose methods aimed to guide an underlying heuristic) and proved to be of practical success in a variety of problem domains and in particular for the approximate solution of NP Optimization problems.