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An empirical study on collective intelligence algorithms for video games problemsolving
(20151231)Computational intelligence (CI), such as evolutionary computation or swarm intelligence methods, is a set of bioinspired algorithms that have been widely used to solve problems in areas like planning, scheduling or ... 
Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints
(20151231)Evolutionary algorithmbased unmanned aerial vehicle (UAV) path planners have been extensively studied for their effectiveness and flexibility. However, they still suffer from a drawback that the highquality waypoints in ... 
On the applicability of ant colony optimization to nonintrusive load monitoring in smart grids
(20151231)Along with the proliferation of the Smart Grid, power load disaggregation is a research area that is lately gaining a lot of popularity due to the interest of energy distribution companies and customers in identifying ... 
Efficient approximation of probability distributions with korder decomposable models
(20160101)During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models. Some of these algorithms can be used to search for a maximum likelihood decomposable ... 
Fitting the data from embryo implantation prediction: Learning from label proportions
(20160101)Machine learning techniques have been previously used to assist clinicians to select embryos for humanassisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve ... 
Joint topology optimization, power control and spectrum allocation for intravehicular multihop sensor networks using dandelionencoded heuristics
(20160101)In the last years the interest in multihop communications has gained momentum within the research community due to the challenging characteristics of the intravehicular radio environment and the stringent robustness ... 
An efficient approximation to the Kmeans clustering for Massive Data
(20160628)Due to the progressive growth of the amount of data available in a wide variety of scientific fields, it has become more difficult to manipulate and analyze such information. In spite of its dependency on the initial ... 
Efficient approximation of probability distributions with korder decomposable models
(201607)During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models. Some of these algorithms can be used to search for a maximum likelihood decomposable ... 
Improved Quantification of Important Beer Quality Parameters based on Nonlinear Calibration Methods applied to FTMIR Spectra
(20160714)During the production process of beer, it is of utmost importance to guarantee a high consistency of the beer quality. For instance, the bitterness is an essential quality parameter which has to be controlled within the ... 
Estimating attraction basin sizes
(20161001)The performance of local search algorithms is influenced by the properties that the neighborhood imposes on the search space. Among these properties, the number of local optima has been traditionally considered as a ... 
A note on the Boltzmann distribution and the linear ordering problem
(20161001)The Boltzmann distribution plays a key role in the field of optimization as it directly connects this field with that of probability. Basically, given a function to optimize, the Boltzmann distribution associated to this ... 
An optimization tool to design the field of a Solar Power Tower plant allowing heliostats of different sizes
(20161030)The design of a Solar Power Tower plant involves the optimization of the heliostat field layout. Fields are usually designed to have all heliostats of identical size. Although the use of a single heliostat size has been ... 
A novel adaptive densitybased ACO algorithm with minimal encoding redundancy for clustering problems
(20161114)In the socalled Big Data paradigm descriptive analytics are widely conceived as techniques and models aimed at discovering knowledge within unlabeled datasets (e.g. patterns, similarities, etc) of utmost help for subsequent ... 
An efficient approximation to the Kmeans clustering for Massive Data
(20170201)Due to the progressive growth of the amount of data available in a wide variety of scientific fields, it has become more difficult to manipulate and analyze such information. In spite of its dependency on the initial ... 
Hybridizing Cartesian Genetic Programming and Harmony Search for Adaptive Feature Construction in Supervised Learning Problems
(20170228)The advent of the socalled Big Data paradigm has motivated a flurry of research aimed at enhancing machine learning models by following very di verse approaches. In this context this work focuses on the automatic con ... 
Multiobjective Optimization of Orbit Transfer Trajectory Using Imperialist Competitive Algorithm
(20170304)This paper proposes a systematic direct approach to carry out effective multiobjective optimization of space orbit transfer with highlevel thrust acceleration. The objective is to provide a transfer trajectory with ... 
Analysis of a hybrid Genetic Simulated Annealing strategy applied in multiobjective optimization of orbital maneuvers
(20170327)Optimization of orbital maneuvers is one of the main issues in conceptual and preliminary design of spacecraft in different space missions. The main issue in optimization of highthrust orbit transfers is that the common ... 
An investigation of clustering strategies in manyobjective optimization: the IMulti algorithm as a case study
(20170330)A variety of general strategies have been applied to enhance the performance of multiobjective optimization algorithms for manyobjective optimization problems (those with more than three objectives). One of these strategies ... 
The weighted independent domination problem: ILP model and algorithmic approaches
(20170601)This work deals with the socalled weighted independent domination problem, which is an N P hard combinatorial optimization problem in graphs. In contrast to previous theoretical work from the liter ature, this paper ... 
Evolutionary algorithms to optimize lowthrust trajectory design in spacecraft orbital precession mission
(20170606)In space environment, perturbations make the spacecraft lose its predefined orbit in space. One of these undesirable changes is the inplane rotation of space orbit, denominated as orbital precession. To overcome this ...