Kuri-Morales A.,Autonomus Institute of Technology of Mexico
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013
The optimization of complex systems one of whose variables is time has been attempted in the past but its inherent mathematical complexity makes it hard to tackle with standard methods. In this paper we solve this problem by appealing to two tools of computational intelligence: a) Genetic algorithms (GA) and b) Artificial Neural Networks (NN). We assume that there is a set of data whose intrinsic information is enough to reflect the behavior of the system. We solved the problem by, first, designing a system capable of predicting selected variables from a multivariate environment. For each one of the variables we trained a NN such that the variable at time t+k is expressed as a non-linear combination of a subset of the variables at time t. Having found the forecasted variables we proceeded to optimize their combination such that its cost function is minimized. In our case, the function to minimize expresses the cost of operation of an economic system related to the physical distribution of coins and bills. The cost of transporting, insuring, storing, distributing, etc. such currency is large enough to guarantee the time invested in this study. We discuss the methods, the algorithms used and the results obtained in experiments as of today. © 2013 Springer-Verlag.
Aldana-Bobadilla E.,National Autonomous University of Mexico |
Kuri-Morales A.,Autonomus Institute of Technology of Mexico
Entropy | Year: 2015
Clustering is an unsupervised process to determine which unlabeled objects in a set share interesting properties. The objects are grouped into k subsets (clusters) whose elements optimize a proximity measure. Methods based on information theory have proven to be feasible alternatives. They are based on the assumption that a cluster is one subset with the minimal possible degree of "disorder". They attempt to minimize the entropy of each cluster. We propose a clustering method based on the maximum entropy principle. Such a method explores the space of all possible probability distributions of the data to find one that maximizes the entropy subject to extra conditions based on prior information about the clusters. The prior information is based on the assumption that the elements of a cluster are "similar" to each other in accordance with some statistical measure. As a consequence of such a principle, those distributions of high entropy that satisfy the conditions are favored over others. Searching the space to find the optimal distribution of object in the clusters represents a hard combinatorial problem, which disallows the use of traditional optimization techniques. Genetic algorithms are a good alternative to solve this problem. We benchmark our method relative to the best theoretical performance, which is given by the Bayes classifier when data are normally distributed, and a multilayer perceptron network, which offers the best practical performance when data are not normal. In general, a supervised classification method will outperform a non-supervised one, since, in the first case, the elements of the classes are known a priori. In what follows, we show that our method's effectiveness is comparable to a supervised one. This clearly exhibits the superiority of our method. © 2015 by the authors.
Acosta-Mejia C.A.,Autonomus Institute of Technology of Mexico
Computers and Industrial Engineering | Year: 2011
To improve the performance of control charts the conditional decision procedure (CDP) incorporates a number of previous observations into the chart's decision rule. It is expected that charts with this runs rule are more sensitive to shifts in the process parameter. To signal an out-of-control condition more quickly some charts use a headstart feature. They are referred as charts with fast initial response (FIR). The CDP chart can also be used with FIR. In this article we analyze and compare the performance of geometric CDP charts with and with no FIR. To do it we model the CDP charts with a Markov chain and find closed-form ARL expressions. We find the conditional decision procedure useful when the fraction p of nonconforming units deteriorates. However the CDP chart is not very effective for signaling decreases in p. © 2011 Elsevier Ltd. All rights reserved.
Palma-Mendoza J.A.,Autonomus Institute of Technology of Mexico
International Journal of Information Management | Year: 2014
A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. Through a literature review a solution is presented here to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) analysis for target process selection. AHP can aid in deciding which supply chain processes are better candidates to re-design in light of predefined criteria. © 2014 Elsevier Ltd. All rights reserved.
Munoz D.F.,Autonomus Institute of Technology of Mexico
Operations Research Letters | Year: 2010
We discuss the asymptotic validity of confidence intervals for quantiles of performance variables when simulating a Markov chain. We show that a batch quantile methodology (similar to the batch means method) can be applied to obtain confidence intervals that are asymptotically valid under mild assumptions. © 2010 Elsevier B.V. All rights reserved.
Morales J.L.,Autonomus Institute of Technology of Mexico |
Nocedal J.,Northwestern University
ACM Transactions on Mathematical Software | Year: 2011
This remark describes an improvement and a correction to Algorithm 778. It is shown that the performance of the algorithm can be improved significantly by making a relatively simple modification to the subspace minimization phase. The correction concerns an error caused by the use of routine dpmeps to estimate machine precision. © 2011 ACM 0098-3500/2011/11-ART7.
Gutierrez-Garcia J.O.,Autonomus Institute of Technology of Mexico |
Sim K.M.,University of Kent
Applied Intelligence | Year: 2013
Service composition in multi-Cloud environments must coordinate self-interested participants, automate service selection, (re)configure distributed services, and deal with incomplete information about Cloud providers and their services. This work proposes an agent-based approach to compose services in multi-Cloud environments for different types of Cloud services: one-time virtualized services, e.g., processing a rendering job, persistent virtualized services, e.g., infrastructure-as-a-service scenarios, vertical services, e.g., integrating homogenous services, and horizontal services, e.g., integrating heterogeneous services. Agents are endowed with a semi-recursive contract net protocol and service capability tables (information catalogs about Cloud participants) to compose services based on consumer requirements. Empirical results obtained from an agent-based testbed show that agents in this work can: successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers' service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants. © 2012 Springer Science+Business Media, LLC.
Fernandez-Duran J.J.,Autonomus Institute of Technology of Mexico |
Gregorio-Dominguez M.M.,Autonomus Institute of Technology of Mexico
Statistical Methods in Medical Research | Year: 2014
In medical and epidemiological studies, the importance of detecting seasonal patterns in the occurrence of diseases makes testing for seasonality highly relevant. There are different parametric and non-parametric tests for seasonality. One of the most widely used parametric tests in the medical literature is the Edwards test. The Edwards test considers a parametric alternative that is a sinusoidal curve with one peak and one trough. The Cave and Freedman test is an extension of the Edwards test that is also frequently applied and considers a sinusoidal curve with two peaks and two troughs as the alternative hypothesis. The Kuiper, Hewitt and David and Newell are common non-parametric tests. Fernández-Durán (2004) developed a family of univariate circular distributions based on non-negative trigonometric (Fourier) sums (series) (NNTS) that can account for an arbitrary number of peaks and troughs. In this article, this family of distributions is used to construct a likelihood ratio test for seasonality considering parametric alternative hypotheses that are NNTS distributions. © The Author(s) 2011.
Balseiro P.,Federal University of Fluminense |
Garcia-Naranjo L.C.,Ecole Polytechnique Federale de Lausanne |
Garcia-Naranjo L.C.,Autonomus Institute of Technology of Mexico
Archive for Rational Mechanics and Analysis | Year: 2012
In this paper we study the problem of Hamiltonization of nonholonomic systems from a geometric point of view. We use gauge transformations by 2-forms (in the sense of Ševera and Weinstein in Progr Theoret Phys Suppl 144:145 154 2001) to construct different almost Poisson structures describing the same nonholonomic system. In the presence of symmetries, we observe that these almost Poisson structures, although gauge related, may have fundamentally different properties after reduction, and that brackets that Hamiltonize the problem may be found within this family. We illustrate this framework with the example of rigid bodies with generalized rolling constraints, including the Chaplygin sphere rolling problem. We also see through these examples how twisted Poisson brackets appear naturally in nonholonomic mechanics. © 2012 Springer-Verlag.
Ramirez-Mireles F.,Autonomus Institute of Technology of Mexico
Wireless Personal Communications | Year: 2012
This paper describes various block waveform encoded (M-ary) signal designs using pulse-position-modulation (PPM) that are useful in pulse-based ultra wideband (UWB) communications in wireless, cable and twisted-pair wire channels, and in other systems based on PPM (not necessarily of UWB nature). This work is focused in four interesting M-ary PPM signal designs: Orthogonal, Equicorrelated, N-orthogonal, and Generic Correlation designs. The designs are based on algebraic constructions with favorable correlation properties, mapping the algebraic constructions into sequences of time shifts to get PPM signals with good correlation properties. For each signal design, the normalized correlation properties are described, the design method is given, and examples of the designs are presented. © 2010 Springer Science+Business Media, LLC.