BackBrowsing by Author "Mendiburu, Alexander"
Now showing items 21-33 of 33
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Instances of combinatorial optimization problems: complexity and generation
Hernando Rodríguez, Leticia
(2015-05-22)
La optimización combinatoria considera problemas donde el objetivo es hallar el punto que maximiza o minimiza una función y donde el espacio de búsqueda es nito o innito numerable. La resolución de estos problemas es de ... -
Kernel density estimation in accelerators: Implementation and performance evaluation
(ACM, 2016-02-01)Kernel density estimation (KDE) is a popular technique used to estimate the probability density function of a random variable. KDE is considered a fundamental data smoothing algorithm, and it is a common building block in ... -
Mateda-2.0: Estimation of Distribution Algorithms in MATLAB
Santana Hermida, Roberto; Bielza, Concha; Larrañaga, Pedro; ; Echegoyen, Carlos; ; Armañanzas Arnedillo, Rubén; Shakya, Siddartha (Journal of Statistical Software, UCLA Dept. Statistics, 2010-07)
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based ... -
MATEDA: A suite of EDA programs in Matlab
Santana Hermida, Roberto; Echegoyen Arruti, Carlos; ; Bielza, Concha; ; Larrañaga Múgica, Pedro; Armañanzas Arnedillo, Rubén; Shakya, Siddartha (2009)
This paper describes MATEDA-2.0, a suite of programs in Matlab for estimation of distribution algorithms. The package allows the optimization of single and multi-objective problems with estimation of distribution algorithms ... -
Multi-objective environmental model evaluation by means of multidimensional kernel density estimators: Efficient and multi-core implementations
; Sáenz Aguirre, Jon; ; ; ; ; ; (2015-01-01)
We propose an extension to multiple dimensions of the univariate index of agreement between Probability Density Functions (PDFs) used in climate studies. We also provide a set of high-performance programs targeted both to ... -
Multi-Start Methods
; ; ; Hernando Rodríguez, Leticia (Springer, 2018-08-27)
[EN]Multi-start procedures were originally conceived as a way to exploit a local or neighborhood search procedure, by simply applying it from multiple random initial solutions. Modern multi-start methods usually incorporate ... -
New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination
Santana Hermida, Roberto; ; (2012-12-27)
Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. ... -
On the application of estimation of distribution algorithms to multi-marker tagging SNP selection
Santana Hermida, Roberto; ; Zaitlen, Noah; Eskin, Eleazar; (2009)
This paper presents an algorithm for the automatic selection of a minimal subset of tagging single nucleotide polymorphisms (SNPs) using an estimation of distribution algorithm (EDA). The EDA stochastically searches the ... -
Optimización de la organización de horarios
(2016-10-26)Ordutegien antolaketaren optimizazioa. Kasu praktikoa: Axular Lizeoa: Axular Lizeoa ikastolako eskolaz kanpoko ekintzen antolakuntza automatikoa (Euskara) -
Solving combinatorial optimization problems using quantum computing: a case study for the QAP
(2020-12-04)Quantum computing is one of the most researched areas in computer science and withone of the greatest future prospects thanks to the new discoveries and methodologies thatcan provide approaches of a different kind to tackle ... -
The Linear Ordering Problem Revisited
Ceberio Uribe, Josu; ; (2014-01-08)
The Linear Ordering Problem is a popular combinatorial optimisation problem which has been extensively addressed in the literature. However, in spite of its popularity, little is known about the characteristics of this ... -
Using network mesures to test evolved NK-landscapes
Santana Hermida, Roberto; ; (2012)
In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances ... -
Zorizko instantzia uniformeak sortzen al dira optimizazio konbinatorioan?
Ceberio Uribe, Josu; Calvo Molinos, Borja ; ; (Servicio Editorial de la Universidad del País Vasco/Euskal Herriko Unibertsitatearen Argitalpen Zerbitzua, 2018)
Konputazio ebolutiboan, algoritmoek optimizazio-problemen gainean duten errendimendua ebaluatzeko, ohikoa izaten da problema horien hainbat instantzia erabiltzea. Batzuetan, problema errealen instantziak eskuragarri daude, ...