Search

The quality indicators of the electrical service are analyzed and managed statistically to generate reports that reflect the deficiencies of the electrical system, which allows the respective improvements to be designed and applied. This work is carried out with the objective of knowing the quality of the technical service in Cuba in the year 2020, as established by UR-BD 0101:2004 of the National Electrical Union (UNE), through the discrete multicriteria optimization method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Its main contribution is the analysis of quality indicators of the technical service in Cuba for the year 2020, with the implementation of the TOPSIS optimization technique, novel in the area of application in the country. Showing satisfactory results when implementing the method and determining which provinces did not comply with the quality levels provided in the year of study. [ABSTRACT FROM AUTHOR]

The article "The emergence of machine learning in physics" by Gorka Muñoz-Gil analyzes how machine learning has impacted society and physics. It highlights the usefulness of neural networks in physics for tasks such as regression, classification, and data generation. Applications in the characterization of physical systems and the optimization of experiments are mentioned, as well as competitions that promote the use of machine learning in physics. [Extracted from the article]

Copyright of Roca: Revista Científico-Educacional de la Provincia de Granma is the property of Universidad de Granma, Departamento Editorial and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this study was to obtain evidence of validity and reliability of the questionnaire for the evaluation of the tutor's competences, through the application of procedures that included unidimensionality analysis, confirmatory factor analysis and a set of techniques indicated for optimization of the measurement of complex constructs. The results indicate evidence of acceptable validity and reliability that allow it to become a measure useful for its large-scale application in the Mexican context. With respect to optimization stage, a reduced scale is supported that contributes to the simplification of application processes. The importance of the evaluation of the tutoring and its contribution to the formative process of the student body with instruments reliable and that allow an appropriate institutional instrumentation. [ABSTRACT FROM AUTHOR]

Copyright of Revista Didasc@lia: Didáctica y Educación is the property of Universitaria de Las Tunas, Centro de Estudios de Didactica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Cubana de Ciencias Informáticas is the property of Universidad de las Ciencias Informaticas (UCI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The objective of this research was to optimize the storage and treatment of information corresponding to the students of the Belén Educational Institution in the municipality of Montelibano, through the design and implementation of a computerized system for disciplinary and academic control. The proposal arises from the diagnosed needs in aspects such as the control of active and graduate student files, the search for data and the generation of reports requested by internal and external personnel. In this quasi-experiment that included the application of pre-test and post-test, a control group of 20 teachers participated, who carried out the activities of recording and processing information in the traditional way, and an experimental group also made up of 20 teachers who used the web platform during the second semester of the year 2020. For the analysis of results, statistical techniques were used, among which frequency tables, percentages and bar graphs stand out, in addition, the ANOVA data analysis was applied, highlighting the significant decrease in completion times of the activities in the experimental group, as well as the satisfaction of the teachers, which allows concluding that the implemented computer system achieved the optimization objective. [ABSTRACT FROM AUTHOR]

The Hierarchical Equal Risk Contribution (herc) approach, as proposed by Raffinot (2017, 2018), is introduced here. Similar to the model proposed by López de Prado (2016), it incorporates machine learning techniques for portfolio optimization, addressing certain limitations of the Mean-Variance model by Markowitz (1952). An application of the herc model is conducted, considering Single and Ward linkage methods for hierarchical clustering of a set of assets traded on the nyse, with companies located in Latin American countries. The results indicate that, for this set of assets, the Ward clustering and hierarchy method is characterized by being intra-country, resulting in a more compact number of clusters compared to the Single clustering method. Additionally, it demonstrates better performance, lower volatility, and a higher Sharpe ratio. [ABSTRACT FROM AUTHOR]

This paper proposes an alternative methodology to optimally design an electrical distribution system in a real urban area. A medium voltage (MV) network polygon is extracted from the web page of a distribution company (GIS platform), which serves as a comparison pattern. A redesign of the medium voltage network is made to the extracted polygon. Taking as a premise that it is a new urbanization that needs to be provided with electric power, with all the technical requirements imposed by the regulating entity, good power quality and at minimum cost. To achieve this goal, two mathematical optimization models are used. The methodology begins by delimiting the project area in a geo-referenced manner; in this area 36 possible sites are located where the distribution transformers that will provide electricity to the new urbanization can be placed. The first optimization model determines how many transformers will be installed, by means of a minimization objective function, the constraints of the model are: transformer capacity (KVA) and coverage (number of subscribers connected to the low voltage network of each transformer). Once the number of transformers to be installed and their respective geo-referenced optimal locations are determined, the model is run. The second heuristic optimization model, based on graph theory, calculates the mine spanning tree for the connection of the medium voltage electrical network, thus interconnecting the transformers of the project with the minimum distance, thus optimizing the construction cost. These optimization models are implemented and solved with Matlab and LpSolve software. The topology found with the two proposed models is electrically evaluated by running power flows with CYMEDIST software. Finally, the proposed model is evaluated by comparing the electrical parameters obtained with the electrical parameters of the polygon extracted from the GIS system of the distribution company. [ABSTRACT FROM AUTHOR]

The problem of the optimal location and sizing of photovoltaic (PV) sources in electrical distribution systems is addressed in this article through the application of the black widow optimization algorithm (BWOA). This problem is of mixed-integer nonlinear nature and is addressed by a master-slave type optimization strategy. In the master stage, the BWOA defines the location and size of the PV generators through discrete-continuous coding, and with this information, the slave stage (power flow for distribution) determines the electrical variables of the system, with which is evaluated the objective function and the constraints of the problem. As an objective function, the minimization of the annual costs of operation and maintenance of the system is considered, added to the total costs of purchasing energy in the electrical network for a planning period of 20 years. The numerical results in the IEEE 34- and IEEE 85-node systems show that with the proposed optimization methodology it is possible to reduce around 27% of the annual operating costs in both systems with the optimal location of three photovoltaic sources. Comparisons with metaheuristics and exact methodologies reported in the specialized literature confirm the efficiency and robustness of the proposed methodology. [ABSTRACT FROM AUTHOR]

Ant Colony Optimization is a population metaheuristic inspired by the behavior of natural ants, specifically their ability to find the shortest path between their nest and the food source. This search mechanism has been tested in discrete problems, establishing itself as a good option for this field of application. In previous works, it was shown that dividing the exploration process of these algorithms into 2 stages considerably improves their performance in terms of time and the quality of the results. In this context, we present, in this work, a generalization of the exploitation process by stages for instances of the Medium and High-Dimension of the Traveling Salesman Problem. For the tests, 5 instances of different sizes were selected and 4 variants of the algorithm were analyzed. The results corroborated that the process of division into stages is good for the performance of the algorithm, reaching the best results with 4 stages. [ABSTRACT FROM AUTHOR]

Copyright of Revista Fuentes, El Reventón Energético is the property of Universidad Industrial de Santander and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Inventum. Ingenieria, Tecnologia e Investigacion is the property of Corporacion Universitaria Minuto de Dios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present study applies a mathematical optimization method to solve the portfolio selection problem. This is formulated as a semi-infinite programming (SIP) problem and is solved by using a version of the stochastic outer approximation method in MATLAB. This method replaces the original problem with a sequence of optimization finite problems. The results are compared with other portfolio selection strategies such as Markowitz. Numerical experiments are performed using five years of data from eight Colombian companies that trade in the stock market. The results show that the SIP portfolio is similar to the minimum variance portfolio and that both are diversified portfolios. The maximum return portfolio is not diversified and should be discarded. Even though the naive portfolio is diversified, its performance and returns are lower than expected, but its risks are less than that of minimum variance and SIP. It is concluded that the proposed method provides satisfactory solutions when compared to the Markowitz method. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources has increased exponentially worldwide. Cuba has implemented a program until 2030 where renewable sources play a fundamental role within the national energy matrix. The policy regarding the installation of solar plants has been to connect small plants of up to 5 MW, mainly in distribution networks. In this work an optimization algorithm is developed to identify the best connection points of small solar plants in distribution networks. The algorithm solves the problem through a power flow combined with a full N-P allocation model. The goal of the algorithm is obtaining the best points to connect solar plants in buses of a radial distribution network at to minimize total active power losses or the deviation of voltage profile. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents a solution methodology for the estimation of parameters of single-phase transformers considering the measurements of voltage and current, for which a non-linear optimization model is used. This model is based on minimizing the mean square error between the measured and calculated voltage and current variables. This nonlinear programming model is solved by implementing the Salp swarm optimization algorithm. The results obtained show that the proposed optimization method allows reducing the error between the estimation of the measured and calculated variables; in addition, the proposed optimization method improves the results presented by other optimization methods reported in the specialized literature. All the simulations were performed in the MATLAB programming environment. [ABSTRACT FROM AUTHOR]

In this article, different optimization techniques were explored through different methodologies. It is important to highlight that optimization problems are found in a large number of academic disciplines and the paths proposed to solve them are found first in the so-called strong mathematical techniques (global optimum) through existence and uniqueness theorems, and the second way, the so-called heuristic or metaheuristic techniques, inspired mostly by biological, social, and cultural processes which allow expanding the search spaces for solutions or relaxing the functions to be optimized from continuous to non-continuous as well as constraints. The metaheuristic technique studied is the particle swarm optimization, (PSO) based on the complete model (cognitive and social components) which is a metaheuristic technique inspired by biology, comparatively with the convex mathematical technique using the behavior of positive semi-definite matrices, for the formulation and modeling of problems with objective functions and convex feasible regions. The problem solved by these two methods consists of knowing the values of the resources of two variables within an objective function. Finally, the answers obtained are evaluated under the assumption that the local minima are global minima within the neighborhood. [ABSTRACT FROM AUTHOR]

Balancing methods for mechanisms have been used over the years to extend the lifespan of machinery by reducing vibration, wear, and fatigue on their components. These techniques have grown in effectiveness but also in mathematical complexity. Nowadays most balancing methods use Cartesian coordinates, which generate complex equations involving trigonometric functions that are difficult to simplify. This paper presents the use of natural coordinates to obtain the balancing parameters of a simplified crankconnecting rod-slide mechanism avoiding the use of trigonometric functions. The balancing optimization of the mechanism is carried out by using a stochastic optimization algorithm based on populations allowing to reduce the Shaking Moment (ShM) by 97.76% and the Shaking Force (ShF) by 94.58%. [ABSTRACT FROM AUTHOR]

A Phenomenological Reading. In this article I will present a working hypothesis that combines Edmund Husserl's and Immanuel Kant's stances on the dimension of the transcendental schema. I will offer a reading that, based on the interpretative proposal of the Argentinian philosopher Martín Arias Albisu, will show how schemata, understood as schema-procedure and schema-product, exhibit a certain similarity to the work that Husserl presented in Philosophy of Arithmetic. In other words, I will describe, on the one hand, how the schema-procedure functions as a representation that encompasses the successive addition that constitutes the unity of one to one, while, on the other hand, the schema-product synthesizes (phenomenologically) empirical multiplicity, i.e., it generates a phenomenal order in accordance with understanding. [ABSTRACT FROM AUTHOR]

Copyright of Documentación de las Ciencias de la Información is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Because the need to explore for the best operational behavior in chemical and food processes, the present research proposes the use of Response Surface Methodology as an optimization tool. Objective: To identify the theoretical, methodological foundation, potentialities and results obtained in Response Surface Methodology application in chemical and food processes development. Materials and Methods: Method theoretical and practical definition was carried out. relationships between input factors for different models in the search phase and surface response adjustment were established. The most appropriate experimental designs and statistical packages were selected and a methodological proposal was made for conducting the optimization supported by its practical example's application. Results and Discussion: Response Surface Methodology theoretical foundation is shown taking into account its sequential character, approximation functions and experimental designs for both independent variables and mixing factors. In addition, optimization techniques according to the model and their application in chemical and food industry researches were considered. The achieved results show the method potentialities in the operational optimum search. Conclusions: The Response Surface Methodology is an extremely versatile technique that allows the use of different experimental designs and statistical tools to solve optimization problems in chemical and food industry processes. [ABSTRACT FROM AUTHOR]

Introduction: Humic acid is an organic origin fertilizer that improves soil conditions and favors the plants development. Filter cake, a waste from sugar production, is a rich and renewable source of organic matter. Objective: To determine operational conditions of humic acid from filter cake extraction process Materials and Methods: The extraction is carried out in two stages, a basic treatment with sodium hydroxide and then with sulfuric acid. A central compound experimental design is planned, with the solid-liquid ratio and treatment time as variable factors. The process is optimized from response surface graphs. Multiple regression analysis is applied to obtain the mathematical models that allow to predict optimal conditions. Results and Discussion: Filter cake had a 74.57%, organic matter content which indicates a high degree of maturation of the organic source; in addition, it presents a pH equal to 6.2 and 65.02% of humidity. The optimal conditions obtained were solid-liquid ratio equal to 0.12 g/ml and 10 h of extraction in each stage, with a humic acid extraction percentage equal to 15.37% and a gross profit of 694.23 $/h. Conclusions: With a 10% level of significance, solid-liquid ratio and extraction time, influence in humic acid from the filter cake extraction process. A 15.37% extraction of organic matter is obtained in humic acid. [ABSTRACT FROM AUTHOR]

The objective of the article is to systematize the optimization of the citrus dehydration process by indirect vacuum drying process by Yara Futuro Agrícola S.A with a Multiple Linear Regression model. The numerical optimization was carried out using the Response Surface Methodology through an experimental design, Box-Behnken, with three factors. The variables defined as: controlled (internal temperature in the drying chamber, internal relative humidity and Vacuum pressure) and not controlled (environmental conditions, citrus inlet temperature, fruit humidity and geometry of the drying chamber). As a result, ANOVA tests revealed that the linear and quadratic main effects of these process variables were highly significant in reducing the drying time. From the results of the statistical tests, the second order regression model was adjusted, with which the optimal parametric configuration of the variables was obtained. [ABSTRACT FROM AUTHOR]

This article proposes a decision-making algorithm as an optimization technique based on a particle swarm (particle swarm optimization-PSO), which allows finding a good solution to the problem of determining the priority (sequencing) of service or manufacturing of jobs scheduling of Flow Shop production systems. The combinatorial nature and complexity of the problem motivates the exploration of other alternative solutions to those traditionally used. Previously defined the objective functions to optimize and the size of the swarm, the position and velocity of the particles are initialized. The objective function is then calculated and the best individual and global positions in the swarm are determined. Finally, speed and position are updated, repeating this procedure according to the number of iterations proposed. The algorithm is developed in Microsoft® Excel® and ®Matlab, achieving better results than those obtained with other methods, such as the service factor, which increases by 19:9% for one machine and 20% for two machines. [ABSTRACT FROM AUTHOR]

Smart Grid is a new concept that seeks to articulate the electrical energy and communications systems as a unified system for the optimization of energy consumption in the world, where one of the most accepted technologies for the transmission of information in residential environments is Power Line Coomunicatios (PLC). The objective of this article is to propose a model supported by queuing theory, which allows evaluating the behavior of multiclass traffic in a HAN (Home Area Network) under the HomePlug AV (HPAV) standard, which is one of the most important standards. of PLC technology. HPAV is considered an efficient standard in hostile conditions for the transmission of information, such as occurs when transmitting through the electrical network, which is why it is very feasible the emergence of packet damming in each node that is part of the PLC network Due to the mechanisms of access to the medium and the availability of a single collision domain, affecting the performance of the network as the number of nodes increases. In view of the above, it is vitally important to have a model that allows describing the behavior that may occur within the PLC network. According to the results obtained, the proposed model allows estimating parameters such as arrival times, waiting times in queue, attention times, probability of packet loss, throughput, number of lost packets, among other values related to the performance of the net. Although the model can be considered of great help for research work related to PLC communications, it could be combined with other more advanced analysis techniques, in order to obtain more profound results and in more complex contexts. [ABSTRACT FROM AUTHOR]

In this work, an analysis is carried out of the importance of minimizing the uncertainty of the availability of the equipment in plants in operation in relation to the operating failures of the plant, which is solved by the inclusion of reliability in the procedure for evaluate investment alternatives to increase the profit of the plant in operation, an aspect that has not been sufficiently addressed in the Cuban oil industry, previously. The proposed methodology is based on a mathematical procedure that made it possible to use software that allows determining the distribution function to which the failures are adjusted, the preparation and optimization of the mathematical model to obtain the number of equipment in each of the stages and finally, compare the gains currently obtained with those that will be obtained when making the necessary redundancies. The validation of this methodology is achieved through an example, which opportunely demonstrates the importance of these new concepts in investment analysis. The example used for methodology validation was the "Sergio Soto" oil refinery in Cabaiguán. The annual availability of the technological system increases with the recommended investments from 0,58 to 0,79 and this implies going up from a feasible annual profit of $ 4,237 206,8 to $ 6,460 933,94. The Excel Solver tools was used. [ABSTRACT FROM AUTHOR]

In this article, we propose the use of the optimization algorithm based on improved pattern search (IPSM), applying it to the estimation of the model parameters of a single diode of a photovoltaic cell. The parameters to be estimated are the photovoltaic current, the saturation current of the diode, the series resistance, the resistance in parallel, and the ideality factor of the diode. The estimation is made from the data obtained from a known curve, that is to say, that a photovoltaic cell could be characterized and from the data of the curve the parameters are extracted. The results are the identification of the parameters and the accuracy of the model concerning the reference at the point of maximum power (MPP). Additionally, a comparison is made with the model obtained with three estimations made with the particle swarm optimization algorithm (PSO), under the same conditions in the number of particles and iterations. The error found shows the similarity of the model with the reference obtained using the IPSM algorithm. [ABSTRACT FROM AUTHOR]

Introduction-- A mathematical model for flexible electrical loads and energy storage system scheduling is presented in this paper, leveraged by the hourly rates according to resolution CREG 015/2018 and analyzed at the residential sector in the context of new demand curves resulting from measures against the COVID-19 pandemic. Objectives-- Three mathematical optimization models are proposed, aiming to find the lowest billing cost for the end-user through flexible load characteristics and seeking optimization through mixed-integer linear programming models. Methodology-- For the calculation of hourly rates, the mathematical formulation described in resolution CREG 015 is implemented and hourly rates are obtained in three different levels following a logic similar to the demand response schemes called Time of Use. Results-- The results obtained show that a demand response program with hourly rates effectively introduces an economic incentive during the evaluated period, through the possibility of modifying consumption patterns that reduce the payment of the electricity bill. Conclusions-- The proposed model of energy demand through scheduling selected flexible loads model and the opportunity to use the energy stored in electric vehicles generates economic benefits for the user by minimizing the cost of energy during the teleworking period in COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Introduction: Food process design has often been approached using methodologies developed for chemical process design. These particularities demand that the design engineer explore other alternatives focused on guaranteeing product quality. In Ecuadorian Amazon context, cane derivatives process is carried out in small artisanal units designed with insufficient technical criteria. This affects final product quality and producers economy. Objective: To propose a procedure that, from the conceptual design, considers product quality. Materials and methods: A procedure was used that considers product quality from the conceptual design, which consists of eleven activities and three decision-making. It is supported by GNU Octave software for process simulation and optimization using the objective function (FO) that maximizes the net present value (NPV) and as a novel aspect, the FO minimizes quality indicators variance. Results and Discussion: In the applied study case, the operational range was determined as: a pH of 3.63 to 4.16, °Brix from 75.12 to 76.73 and NPV fluctuates between 2 603 469.38 USD to 6 669 971.27 USD with a sigma level greater than three. Conclusions: Uncertainty of operational variables decrease increases product acceptability and this is reflected in optimal values obtained from the NPV and quality attributes. [ABSTRACT FROM AUTHOR]

Introduction: A number of alternatives arise daily on how to control transformative process in chemical process industry. To help in decision-making process, some calculations are carried out to estimate energy, technological or environmental indicators and then choose the best variant. Present investigation proposes mathematical methods use, mainly optimization, using linear programming as a tool in these decisions. Objective: To show linear programming applications in solving Chemical Processes industry problems. Materials and methods: Procedures used in Chemical Engineering doctorate defenses and articles derived from these investigations were used as this investigation basis. Results and Discussion: Results achieved by researchers using linear programming are detailed for each four directions in which uncertainty has been classified in Chemical Engineering according to Rudd and Watson. Investigations are grouped and offered for each classification: research problem, necessary requirements for its application, investigations carried out in each work direction and achieved results. Each applications group, according to uncertainty problems considered, has common features and restrictions. Conclusions: Linear programming is a versatile tool for solving uncertainty problems in chemical industry that is and will be present in traditional chemical industry facilities into more efficient facilities transformation procedures. [ABSTRACT FROM AUTHOR]

In this article a methodology for estimating electrical parameters in distribution transformer is presented by considering voltage and current measures through the formulation of a nonlinear programming (NLP). This mathematical optimization model is developed by applying the Kirchhoff's laws to the equivalent electric circuit of the transformer. To solve the NLP model the general algebraic modeling system widely known as GAMS is used. The proposed methodology is developed in a tutorial sense by presenting a numerical example that corresponds to a single-phase transformer with 20 kVA and a transformation ratio about 8000/240 V. Numerical results show that the parametric estimation in the transformers with the proposed NLP model represents the electrical behavior of these devices adequately considering different load scenarios. All the simulations were carried-out in GAMS version 25.1.3 licensed by Universidad Tecnológica de Bolívar. [ABSTRACT FROM AUTHOR]

Multiple Sequence Alignment (MSA) is one of the main topics in the in bioinformatics domain, consists finding an optimal alignment for three or more biological sequences with the number maximum of conserved zones or totally aligned columns. Different scores to assess the quality of the alignments have been proposed, so the problem can be formulated and resolved as a Multi-Objective Optimization Problem (MOP). For this reason, in this paper we present a Multi- Objective approach applied to MSA. We have considered state-of-the-art optimization algorithms aimed at solving different formulations of the MSA: NSGAII, NSGA-III, SPEA2, MOCell, SMS-EMOA, MOEA/D and GWASF-GA. Furthermore we have considered some popular metrics as objectives to be optimized: The weighted Sum-Of-Pairs with a ne gap penalties (wSOP), the Totally Aligned Columns (TC), STRIKE and BaliScore. Finally we have described the main features of our software jMetalMSA, a Multi-Objective optimization software tool applied to MSA problem and illustrated a working example for experimentations purposes. [ABSTRACT FROM AUTHOR]

Copyright of Ingeniería (0121-750X) is the property of Ingenieria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents an approach to one of the most important unresolved problems that has been formulated for this century. The restricted three body problem was considered and periodic orbits were found around the points of stable equilibrium between different planets, where a spacecraft would need little energy to move. Some very ecient techniques were implemented for the optimization of multivariate functions and the integration of differential equations. Very good results were obtained and it is shown that the used methods reduce the computing time considerably. [ABSTRACT FROM AUTHOR]

This paper presents a multivariate UPD estimator, family member [A,U,T] with parameters p and s, which allows to calculate simultaneously parameters of Weibull K and C at a point Pe from the measured values of these variables in several sampling points. During the 3D estimation, the spatial relationship between the data and the associated values of elevation and roughness of the terrain is taken into account; with the estimated results, a model of wind energy resources is developed, given by a 3D mesh where to each node is associated the values of K and C. Finally, a method of combinatory optimization is described to find the values of p and s such that the mesh model is feasible and optimal for the given data. [ABSTRACT FROM AUTHOR]

Mathematical Model of a Series-Parallel (SP) photovoltaic (PV) generator represents each module through an equivalent electrical circuit denominated single diode model, this model has associated a nonlinear equation system that describes the electrical behavior of SP generator. This paper presents a solution of this system using optimization methods widely using: Trust Region Dogleg and Particle swarm optimization (PSO) for solving the electrical model of PV generator operating under homogeneous or non-homogeneous conditions, changing the number of submodules and shading pattern. It has been made simulations about generators composed by 3 and 15 series submodules, operating under different partial shading conditions. Between the implemented methods, Trust Region Dogleg show a better performance than other methods, with 2 and 14 times less computation time than the reference method and PSO, respectively, and a RMSE equal or 50% lower than PSO. [ABSTRACT FROM AUTHOR]

Proper management of projects has become an element of vital importance for the solution to problems of society. In this context, there are two main objectives to be solved: the construction of project plans which may comply with the constraints of the problem and the optimization in terms of cost and time of those plans. To this end, all activities of project must be organized in such way that the constraints related to the precedence among them and the availability of renewable and non-renewable resources at each instant of time are met. The aim of this paper is to present an Estimation of Distribution Algorithm (EDA), which incorporates the handling of the constraints in the probabilistic model, for the construction of optimal or quasi-optimal project plans. For the validation of the algorithm, authors used both the PSPLib database repository for the development of the scheduling research and the databases of projects of the Repository for Research in Project Management, University of Infomatic Sciences. [ABSTRACT FROM AUTHOR]

The active aromatic components from commercial samples of sacha inchi oil obtained from Santa Rosa de Osos (Antioquia, Colombia) crops were identified by solid phase microextraction technique coupled to gas chromatography, mass spectrometry, and olfactometry (HS -SPME-GC-MS-O). In the optimization of the extraction technique, the following conditions were defined: SPME fiber of divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS), extraction temperature 50 °C, and exposure time 40 min. Under these conditions, a total of 20 active aromatic compounds were found, which include E-2-octenal, E-heptanal, (E,E)- 3,5-octadien-2-one, hexanoic acid and (E,E)- 2,4-heptadienal as the components with the greatest contribution to the aroma formation of sacha inchi oil. [ABSTRACT FROM AUTHOR]

This work was proposed as the first objective to demonstrate that a consistency index proposed in 2015 as part of an attribute weighting model is not objective enough. The second objective is the proposal of a new optimization model to weight attributes that is based on an idea similar to that of the analyzed model where the limitations detected in it are not evident. To achieve the above, the significance and scope of the consistency and inconsistency indices proposed in the previous work from where the limitation was induced in the first one is corroborated with the analysis of a case study. The new model is based on extended fuzzy logic techniques and on new concepts introduced by the authors such as the weighted generalized inconsistency index of order q and the internal and external confidence coefficients. [ABSTRACT FROM AUTHOR]

FuzzyPred is an unsupervised-learning data-mining algorithm, which allows extracting fuzzy predicates in normal forms from the data. This method is used to solve a descriptive task where it is not known the kind of relationships that are to be found. The goal is to find patterns that describe the data and their relationships. Due to the large set of solutions or search space that may have, it was modeled as an optimization problem, where metaheuristics are applied to find good solutions. FuzzyPred provides as a result a set of predicates, evaluated in each of the quality measures, in spite of the fact that only one of the measures is optimized (truth value). This paper introduces a multiobjective approach for FuzzyPred by using two of the most known multi-objective optimization techniques: Pareto technique (or pure multi-objective) and weighted factors. An experimental study is presented in order to compare the efficacy of both techniques in this problem. The results in several international databases show that better results are obtained by the pure multi-objective technique. [ABSTRACT FROM AUTHOR]

one of the techniques to treat oil from oil wells is to use oil treatment trains to separate the three existing phases: gas, oil, and water. One of the equipments that make up the train is the three-phase separator. This work demonstrates the feasibility of using a hierarchical control scheme for an online setting of optimal pressure and temperature setpoints and thus reducing energy consumption in the heat treater. So that the manipulated variables and the set points are within the limits of the safe operation, with this provides an economic and environmental benefit for this plant. The achievement of this optimization is the main contribution of this work. For the development of this work we designed an optimization algorithm based on three hierarchical layers where the first layer refers to direct control (PIDs), the second layer refers to the optimization of steady state objectives (SSTO), the third layer refers to local optimization of objectives (LSSO). For the solution to this problem, we resorted to solutions of linear optimization and nonlinear optimization these algorithms are related to the linearized model of the plant, in other works are usually based on the theory MPC (Predictive Control Model). The simulation of the algorithms was done in Matlab and tested in a simulated plant in Hysys using the Active x server connector that connects the two software. In this experiment, it was possible to save 30% of energy consumption. In turn, it was found that it is possible to relate the plant model with the linear and non-linear optimization algorithms, which concluded that the implementation of these algorithms is feasible in this type of plant for process optimization. [ABSTRACT FROM AUTHOR]

The teaching of optimization, has usually become a mechanical process and devoid of arguments: in general their uses are ignored in specific situations of other disciplines, such as engineering. With the Socio - Epistemological Theory, we make an empirical investigation, where the epistemology of uses is problematized to value the functional justification demanded by other domains of knowledge. We analyze aspects of the Lagrange Analytical Mechanics work and the work of mechatronic engineers. Engineers in training were defined as the study community and the emergence of a specific selection situation is supported as its uses and meanings of optimization. The methodology consisted in the technique of documentary analysis and semistructured interviews. It was found that selection situations generate optimization meanings and arguments. [ABSTRACT FROM AUTHOR]

The new labeling rule in Colombia RETIQ Art. 12 Three-phase induction motors type squirrel cage for 60 Hz, requires that induction motors specify their efficiency under nominal conditions. The International Electrotechnical Commission (IEC) indicates three ways to compute induction motor efficiency. One of these ways considers in detail each of the power losses in the motor. It is clear that, from the standpoint of manufacturers, it would be advantageous to know the detailed power losses in order to improve motor efficiency. Furthermore, the measurements made to compute power losses provide enough information to estimate the electrical parameters of induction motors, using optimization algorithms. This work explores parameter estimation of induction motors using the measurements indicated by the IEC to estimate power losses in induction motors. In particular, the algorithms of global optimization: harmony and hybrid genetic algorithms produce consistent estimates of the electrical parameters of the induction motor. Once the electrical parameters of the induction motor are found, its performance can be modeled for any load condition, including transient states. [ABSTRACT FROM AUTHOR]

In this study we analyze the performance of three free and open source optimization solvers: lpSolve, GLPK and Cbc. We use 4 datasets with instances corresponding to 4 configurations of a container yard located in Villa Clara, Cuba. It is analyzed if the Storage Space Allocation Problem for import containers in can be solved, in a acceptable computational time for the operations of a real container yard, using an exact optimization method. We base our evaluation on three metrics achieving an optimal solution on import containers: Computational time, number of iterations, and number of nodes. Moreover, we present a feasibility study on the impact of the exact method in the operations of container yard in Villa Clara. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of applying the optimization of mean-variance mapping technique in the problem of estimating the parameters of the soil model of two horizontal layers. This problem consists of determining the parameters of the soil model from experimental measurements of apparent resistivity obtained with Wenner method, minimizing the mean square error between values of the experimental and theoretical resistivity curves, which are calculated with mathematical expressions and soil parameters acquired through the optimization of mean-variance mapping technique. Several tests were carried out with resistivity measurements that correspond to different soil types, the results were contrasted with those reported in the technical literature and metaheuristics implemented. In conclusion, according to the results, the performance of the optimization of mean-variance mapping technique was found to be superior than other analyzed optimization techniques. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencia y Tecnología is the property of Revista de Ciencia y Tecnologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the optimal location and sizing of distributed generators and capacitor banks in radial distribution networks to minimize the active and reactive power losses. A mixed-integer nonlinear mathematical model is proposed to formulate the problem. This mathematical model is solved through general algebraic modeling system (GAMS) and the CONOPT solver. GAMS implementation is presented with 10 nodes test system classical used in the specialized literature. As test system, the 33 nodes system is used under three simulation scenarios. The first simulating scenario consists only in the location of distributed generators, while the second scenario evaluates only the location of capacitor banks and the third scenario combines both elements. The simulation results obtained show that the integration of both elements improve significantly the operating features of the system by comparison with the first two scenarios analyzed. [ABSTRACT FROM AUTHOR]

Software testing can exceed 50% of the total cost of a software project, which is why companies need an alternative to reduce their cost and time of implementation. This research proposes the use of combinatorial structures known as Covering Arrays (CA) and Mixed Covering Arrays (MCA), which guarantee the detection up to 100% of errors with a minimum amount of testing. With this approach, a Visual Studio.NET add-on was developed for the optimization of the tests and its use was evaluated with students of last academic term of Computer Science Engineering and of a software company. The results obtained are promising and motivate the research group to disseminate its work at the national level. The research project was funded by the Vice-Principal Office of Research of the Universidad del Cauca. [ABSTRACT FROM AUTHOR]