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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

With the simulation and optimization of a manufacturing system, the input parameters are sought to obtain the best performance of the system, considering in many cases a single objective or measure of performance. However, many decisions involve multiple criteria, usually in conflict. Currently, companies are required to improve their profitability as well as to reduce their impact on the environment and use energy rationally. In this paper, the wood products manufacturing process of a small company was studied to determine redesign alternatives, with simultaneous economic and environmental criteria. A simulation model of the system was built, which was validated and verified, and an optimization model for it in which two objectives were combined in a single function, incorporating in it the preferences of the decision makers with respect to each criterion. Results expose that combining both criteria it is possible to achieve substantial improvements in the benefit, at the same time that generating less emissions than if only the economic objective were pursued. It is concluded that simulation and optimization combining both criteria can improve economic-environmental performance in wood manufacturing systems, even in small companies. [ABSTRACT FROM AUTHOR]

In search for a satisfactory answer to the question: How much debt is appropriate for a particular company? Researchers had development a whole wealth of literature that addresses the problem using different approaches. Research on financial structure and its impact on the corporate value of the companies began with the contributions of Franco Modigliani and Merton Miller which laid the foundations of the new approach of modern finance and has allowed the development of new regulations aimed at theories search for an optimal financial structure. This paper proposes a mathematical algorithm based on the Bellman's Optimality Principle, which allows companies to determine the proportion of debt and optimal capital so that its weighted average cost of capital is minimized, which is equal to maximize its market value. [ABSTRACT FROM AUTHOR]

The main objective of this work is the illustration of textual statistical analysis in confronting of the speeches of three great theorists of the world economy; it is aimed to review the emphasis from semantic segments that characterize the speech of each one. In this study, through a correspondence analysis, textual variables from the selected papers were identified, which are presented as characterizing the main concepts that establish patterns in each discourse. The results show the power of this methodology for applications in economics. [ABSTRACT FROM AUTHOR]

Shell and tube heat exchangers (STHEs) are the most common type of heat exchangers. They are applied in many industrial facilities. The minimization of the costs of these heat exchangers is a key objective for both designers and users. The heat exchanger design involves complex processes, including selection of the geometric parameters and operating parameters. The traditional approach to design shell and tube heat exchangers is evaluating a number of different geometries of the exchanger to identify those that meet a requirement of heat and a set of geometric and operational constraints. However, this approach is slow, inaccurate and does not guarantee an optimal solution. In this paper is analyzed a procedure for designing heat exchangers and develops the economic optimization of the data by the method of simulated annealing. It was considered as the objective function the minimization of the total annual cost. For design optimization were considered as independent variables the inner diameter of the shell, the outer diameter of the tube and the spacing between the baffles. Also were considered to optimize two provisions or arrangements of tubes: in a triangle and a square. In this paper it is also presented an example of optimization of a heat exchanger. The results of the optimization using simulated annealing technique are compared with those obtained using particle swarm and genetic algorithms. [ABSTRACT FROM AUTHOR]

When we face an optimization problem whose de finition (in some aspect) changes over the time, we are in the presence of a Dynamic Optimization Problem (DOP). The aspects that can change are the objective function, the variables' domain, the appearance/disappearance of variables or constraints, etc. This paper aims at providing a first introduction to those who are interested in the topic. Concretely, we present the DOPs, the most common performance measures as well as the methods used to solve them. We also briefly describe some of the most recent reviews and comment some current challenges and research opportunities in DOPs. [ABSTRACT FROM AUTHOR]

As the classical water-supply looped-network optimization problem is mathematically nonconvex and multimodal, the resulting solution of most approaches is uncertain in the sense of how close it is to the "best" solution. In many cases, this "best"' or "global" solution is invoked and pursued without a clear understanding of its meaning. This paper discusses what is involved in "global" solutions and the role that pipe flow distribution can play to deal with nonconvexity and multimodality in a new context. The author has introduced this new context recently after formulating a new objective function capable of finding that a looped network can be economically more attractive than its related branched one. Therefore, the convenience of an approach dealing with flows and heads, as relevant decision variables, is encouraged in this paper and its advantages enumerated under the new concepts. The entropy approach is studied critically and an example is provided for comparison with the proposed approach. [ABSTRACT FROM AUTHOR]

The objective of this paper is to show a methodology that allows finding the optimal behavior of a system, given a measure of effectiveness and a set of controllable variables. In the paper simulation techniques are combined with experimental design to produce a response surface, and after an optimization method is applied. A case study in the Cuban sugar industry is described. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective mixed integer non-linear problem (MINLP) to design the sustainable supply chain for recycling several products. This model integrates economical and ecological objectives to support strategic and tactical decisions such as facility location, material flow design and transport selection. The environmental impact is assessed through the Life Cycle Assessment (LCA) methodology using the Eco-indicator 99. A case study to design a supply chain for recycling two kinds of plastic was modeled, the constrain method was used to build the Pareto curve. In the case study were shown a set of indicators to assess the solutions for better supporting of decision-making process. [ABSTRACT FROM AUTHOR]

This paper analyzes the effect of different configurations of initial conditions for the optimization algorithm based on particle swarms with vorticity behavior. The proposed algorithm combines the gradient-based search and particle swarm behavior, thus, this algorithm can be affected by the initial conditions for the particles. Finally, a 2D test function is used to observe the characteristics of the algorithm. [ABSTRACT FROM AUTHOR]

The purpose of the optimum designs is to determine the optimal experimental conditions in terms of minimum variance of the estimated vector of parameters, so that statistical inferences can be generated as accurate as possible. This theory presupposes knowledge of the function relating the explanatory variables with the response variable. In this situation, usually get designs with support points as parameters in the model. Since p-point designs assume that the model function is known, these could not be optimal in some practical situations because they do not allow to test the goodness of fit of the assumed model. In this paper we present a generalization of the methodology proposed by to increase the number of support points in D-optimality criterion. An expression for the variance of the predicted response in terms of a constant δ will be provided, which allow to determine the points to be added to the D-optimal design. We propose a strategy for choosing δ. Finally we provide a pseudo-optimal design with (p + s) support points. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for optimal relocation of transformers in distribution systems. The problem is formulated as an optimization model of multiobjective non-linear integer type, which considers investment and operating costs, and the benefit of the concept of assets to be recognized by usage charges as stipulated in Resolution CREG 097 of 2008. The model is solved using the multiobjective optimization algorithm NSGA II. To check the validity of the methodology, a real distribution system belonging to an electric utility in Colombia is used, which takes into account both single and three phase distribution transformers. The results compared with respect to the case without considering the relocation of distribution transformers, reflect the importance of this methodology and its benefits to the distribution companies, and serves as a support tool for compliance with the standards set by regulatory bodies that define the appropriate chargeability of distribution transformers. [ABSTRACT FROM AUTHOR]

This paper proposes a new methodology to solve the problem of electric transmission network expansion planning by adding specialized restrictions that use information associated with operational areas of the electrical system. The new set of restrictions reduces the computational effort required to solve the problem, allowing that the problem solving techniques perform better in the search for the optimal solution. This new set of restrictions generates cuts in the solution space that eliminate low quality regions. To validate the methodology, a test system of the specialized literature is used. The results presented show the good performance of area-based restrictions. [ABSTRACT FROM AUTHOR]

This paper presents an optimization method for detecting SIFT points (Scale-invariant feature transform), by using a GPU parallelization. taking advantage of multiple cores of it, to divide the processes using the API's CUDA. The goal is to accelerate the computation time, which is a critical variable for the entire process of key-point's detection. The strategy used is based on two assumptions, the load balance and distribution of calculation. Each thread will perform the operations required for calculating SIFT and obtain the necessary descriptors according to an appropriate threshold. Parallelizing the process of assignment of orientation, which consists of the accumulation of all the orientations concerning a region of a key-point, assigned to each pixel in the window a thread, centered on the location of a key point, was worked inside SIFT. The tests were performed with a Notebook with Core 2 Duo 2.2GHz, 3GB of RAM and a GeForce 8600GT VGA (32 Cores) 512MB. The results obtained show that performance is achieved in terms of speed of the order 42.5 millisecond on average, considering all tests and all resolutions worked (320x240, 480x360,640x480, 800x600, 1024x768, 1280x960), where the parallelization of SIFT, shows no significant loss of key points, compared to the sequential version. [ABSTRACT FROM AUTHOR]

In this paper we identified the best conditions for the removal of Acid Blue 9 dye (AB9) using flower wastes (FW) as an adsorbent were determined using a full factorial 2³ and a Box-Behnken design for further optimization. Adsorbent dose (D), dye concentration (C) and contact time (t), were the assessed variables. The dye content was quantified by UV-Vis spectrometry. The statistical model presented an adequate adjustment coefficient (R² = 99,18%), allowing to achieve a removal of 98,5% with a dosage of 7,8 gL-1, dye concentration of 7,11 mgL-1 and contact time of 104 min. These results suggest that flowers wastes are an alternative and potential adsorbent material for the treatment of dissolved acid dyes. [ABSTRACT FROM AUTHOR]

In this paper we propose the formulation of a model for urban double travel distribution delimited at origin and destination, based on the maximization of entropy and minimization of the generalized travel costs by relaxing the condition that such costs are a parameter, extending the formulation under the assumption that they are fuzzy variables with an intervalar function. In addition, given such assumptions, we propose a formulation of an optimization model associated with discrete choices, and we present a proposal for using the model in predictions. A numerical example is developed for explaining the theory developed. [ABSTRACT FROM AUTHOR]

In this paper, a comparative analysis on the use of four metaheuristics for obtaining an optimal adjustment of a fault locator based on support vector machines (SVM), is presented. This research is aimed to determine those techniques which help to obtain the best performance at the specific problem of fault location. The proposed fault locator is tested in the 34 nodes IEEE power distribution system where the average precision obtained considering the best alternatives is around 99%, using a database of 13824 registers from single phase, phase to phase, two phase to ground and three phase faults. The comparison of the parameterization alternatives shows how those metahueristics based on population have better performance that those based on trajectory, having a good performance in all of the tested situations. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to solve the problem of service restoration in electric distribution systems, which is proposed as a model of mixed integer non-linear optimization where the objective function is to maximize the load that is outside of service, subject to a set of technical and operational constraints. The problem is solved using heuristic techniques, through sensitivity indicators that guide the restoration process. The methodology is validated in distribution systems, finding good-quality results. [ABSTRACT FROM AUTHOR]

In this paper, we present a modification of the repetitive random search algorithm. In our proposal, we change the fixed parameters which values are set by the user, by deterministic values following a chaotic map. The proposed algorithm is used to optimize four well known test functions for 10, 20 and 30 dimensions. For all cases, our proposal converges to better points that the optimal points obtained using the traditional version with fixed values in the parameters. The obtained results encourage us to continue the development and testing of the proposal algorithm with a major suite of test functions, and to compare it with other well established heuristic algorithms. [ABSTRACT FROM AUTHOR]

The paper discusses the conception and original design of the Isotope Centre's facilities, and structural changes made to the centre over 15 years of operation with the aim of meeting the Good Manufacturing Practices Regulations nonexistent at the time of its commissioning. Particular emphasis is given to the changes made to hot cells, glove boxes, and also some aspects related to technological processes. As a result, the CENTIS productions fulfi l international standards and its facilities have been validated in correspondence with the national regulations. Steps are directed not only to meet the requirements of ISO 9000 and GMP, but to ensure optimization and fl exibility in the use of the facilities [ABSTRACT FROM AUTHOR]

In this paper an algorithm for the numerical solution of nonlinear equations systems is presented. For this purpose the system of equations becomes a function of real value which will be minimized, in the global sense, in a given initial domain (a box in n) using analysis of intervals. The designed algorithm has the ability to determine the existence or not of solutions to the system of equations in a given box. The solutions of the system of equations, if they exist inside the given box, are expressed by means of enclosures by sub-boxes whose size is smaller than the established accuracy. There is not restriction about the relationship between the number of equations and the number of unknowns of the system. It is also carried out an analysis of the convergence of the algorithm, and the results of their application are shown for some test problems. [ABSTRACT FROM AUTHOR]

Hydrogen is an attractive energy source due to its high energy content and friendly combustion. Among the various mechanisms for hydrogen production, dark fermentation is one of the most interesting, because it uses the wastes as feedstock. The research on hydrogen production is to date in study, but the results are not yet conclusive. In this sense, this paper aims to do a critical review between 1993 and 2011 to show the most studied factors, the configurations most employed and the main results on this topic. Our findings showed the need, not only to optimize the factors that influence the production, but also to do more studies on real scale and in continuous flow. [ABSTRACT FROM AUTHOR]

This paper presents a way of detecting innovation opportunities for assistive products for personal mobility applying the laws of technical evolution. These laws are formulated in the theory of inventive problem solving, TRIZ. The products belong to class 12 of UNE-EN ISO 9999 standard and the analysis is made in conjunction with engineers and industrial designers. This study proposes an innovative way to represent the technical system of this type of mobility aid products as a whole, this is, as a machine-human integral unit. The results obtained show innovation opportunities in the following fields: optimization of transmission systems, movement control and brake system, high efficiency energy use and improvement in the accessibility levels, both, from user to product and from product to environment. [ABSTRACT FROM AUTHOR]

This paper presents a methodological approach for tuning fuzzy classifiers intended to recognize the Australian sign-language considering two particular contexts. We describe the fuzzy classification architecture and the tuning process based on differential evolution. The validation results show that it is possible to find a fuzzy classifier whose classification error is around 13.0% over a group of words taken from several experts for each interaction context. This characteristic is relevant as previous works only considered recognizing words provided only by one interpreter. [ABSTRACT FROM AUTHOR]

In this paper a method to solve the state estimation problem in electric systems applying combinatorial optimization is presented. Its objective is the study of measures with difficult detection errors, which affect the performance and quality of the results when a classic state estimator is used. Due to the mathematical complexity, sensibility indicators are deduced from the theory of leverage points used in the Chu-Beasley optimization algorithm with the purpose of reducing the computational effort and enhance the quality of the results. The proposed method is validated in a 30-node IEEE system. [ABSTRACT FROM AUTHOR]

This paper presents a new tool, developed and optimized in order to observe and analyze the code block in volleyball. This tool has been developed in the context of observational methodology, enabling the monitoring and analysis of the action in volleyball blocking technique, allowing discerning observable factors have greater impact on the performance of such action. The research was developed using an inductive empirical strategy. The optimization process of the category system includes data quality control, emphasizing the application of generalizability analysis. This tool is useful for sports psychologist because it allows a proper evaluation of the technical gesture. [ABSTRACT FROM AUTHOR]

The economic advantages of a looped network have not been considered in any of the optimization models found in the literature. This paper introduces a new formulation and methodology in an attempt to give a practical solution to this problem. The new formulation consists of a non-linear optimization model solved by classical differential calculus and the Newton-Raphson technique. An example shows how the looped network can be less costly than a branched one. Previous research usually optimizes the network for a given design demand. Also the value that should be specified as the desired network reliability has not been reported so far. This work introduces a methodology to obtain not only an adequate value for the reliability of a looped network but also the appropriate design demand as well based on a thorough cost analysis. A second example illustrates the detailed performance of this methodology. [ABSTRACT FROM AUTHOR]

In this paper we face a problem that considers the selection of several bus stops from many potential ones and the respective design of optimal routes for the bus transportation of personnel from the surroundings of their houses to the place in which they work. We propose an integer programming model for the mathematical formulation of the resulting location-routing problem. The proposed location-routing model is suitable to solve little and medium size instances of the problem. However, to face large size instances of the problem an alternative strategy is needed. For that purposes, we propose a hierarchical scheme by solving a set covering location model for the bus stops selection, followed of another one for the design of routes based on the previous bus stops selected. To solve the vehicle routing problem we also incorporate the heuristic of Holmes and Parker for the resolution of larger instances of the problem. The alternative strategy does not provide the global solution to the problem but it is easy to apply and essential to face larger instances of the problem. [ABSTRACT FROM AUTHOR]

The study of mass transfer should be started from the viewpoint of transport phenomena followed by macroscopic separation processes. To develop the transport phenomena area it is necessary to advance in mathematical analysis and computational tools for processes design and optimization. Computational fluid dynamics (CFD) is a versatile and, accurate choice, which has evolved in recent years to obtain a growing interest in the scientific community of food engineering. This paper shows an overview of the fundamentals of mass transfer and CFD applications in mass transfer operations of food industry, based on the available literature on the Science Direct, EBSCO and Scielo databases between 1999 and 2009. There has been considerable growth in the development and application of CFD in drying and refrigeration areas. [ABSTRACT FROM AUTHOR]

This paper proposes a numerical method for the calibration of dynamic stochastic general equilibrium (DSGE) models. The method consists in the use of a hybrid algorithm, first to find the steady state, and then to minimize an objective function defined by the researcher according to the purposes of the calibration. The proposed method consists in the use of the Simulated Annealing algorithm followed by traditional optimization routines. The virtues of the algorithm are analyzed through Monte Carlo simulations, using a closed-economy model that has a steady state with no analytical solution. The results obtained in this exercise show that the proposed algorithm generates more precise results using less computational resources than traditional alternatives. Finally we present the calibration of a model for the Colombian economy, consisting of 179 equations and adjusted through 50 parameters to replicate 50 ratios. The maximum percent deviation of the steady-state ratios of the model with respect to the corresponding values in the Colombian economy is 7.9%, and in 29 of all the 50 cases this deviation is less than or equal to 1%. [ABSTRACT FROM AUTHOR]

This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem) structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic. [ABSTRACT FROM AUTHOR]

Finding the peak of an optimization problem or model is just part of the solution process. This paper analyzes dual prices, objective function coefficients, the reduced cost of each variable, sensitivity ranges, and the width of the values in the right side of restrictions by means of a computer program, and a profit maximization lineal programming model applied to an agricultural business. The post optimal analysis reveals vital information to farmers who operate in a dynamic context for the best decisions to be made in regards to variation options of determined parameters in a model of a future project to upgrade the optimum value of the objective function. The agricultural producer gets to know how the optimal production plan may remain the same while increasing profits that are subject to variations in the boundaries of the problem or the business itself. He gets to assess the real needs of available resources and might find out what would be the best choices and decisions to improve the optimal value when simultaneously considering the marginal profit that the dual price represents and the allowed increase in the value on the right side of each restriction. [ABSTRACT FROM AUTHOR]

PCA and LDA are two of most widely used techniques for face recognition with IR images. In this paper we report the results obtained by using Genetics Algorithms for optimization the characteristic vector generated by these techniques, by assignation of weights to each vector according its performance in the classification task. It shows that, under the proposed scheme, is able to obtain a lower classification error compared to conventional method. [ABSTRACT FROM AUTHOR]

Evolution Strategies is a bio-inspired, robust, and efficient technique for solving optimization problems where the solution space is unrestricted. However, this assumption is unreal in many cases because the solution space is limited by complex boundaries in the form of linear and non-linear restrictions. In this paper, a modification of the original algorithm of Evolution Strategies for optimizing problems where the solution space is bounded using complex restrictions is proposed. The proposed method is based on the use of a penalization function which is zero inside of the feasible region and equal to the maximum value inside of the feasible region when an unfeasible point is considered. The proposed approach is proved using six benchmark problems. In all cases, our approach found an optimal point equal or lower than the values reported in the literature. [ABSTRACT FROM AUTHOR]

The advance in the knowledge and technology is growing quickly and greater quantity, so it is difficult for the health professional to access to whole information that is generated every day on diagnostic and therapeutic strategies more effective, so the clinic practice guidelines (CPG) is a resource to support the updating of the health professional and support them in making clinical decisions. The CPG is also a better support to the manager of health services in making decisions regarding the strategies that have performed for the patient and less risk to the individual and collective health. They also support the response capacity of the medical units and hospitals and guide the planning of services to the optimization of the resources. This paper summarizes the methodology of a national project for the development of GPC coordinated by the Mexican Social Security Institute with the collaboration of more than 1200 health professionals of the institution in a great effort institutional update and make information accessible to the entire health sector, which also defines the steps to upgrade and maintain the updating of knowledge and technology expressed in them. [ABSTRACT FROM AUTHOR]

This paper provides information about the efficacy of a tutorial training program intended to enhance elementary fifth graders' study processes and foster their deep approaches to learning. The program «Testas's (mis)adventures» consists of a set of books in which Testas, a typical student, reveals and reflects upon his life experiences during school years. These life stories are nothing but an opportunity to present and train a wide range of learning strategies and self-regulatory processes, designed to insure students' deeper preparation for present and future learning challenges. The program has been developed along a school year, in a one hour weekly tutorial sessions. The training program had a semi-experimental design, included an experimental group (n=50) and a control one (n=50), and used pre- and posttest measures (learning strategies' declarative knowledge, learning approaches and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge of learning strategies and in their deep approach to learning, consequently lowering their use of a surface approach. In spite of this, in what concerns to academic achievement, no statistically significant differences have been found. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective analysis including variables of the environment of the energy system which is conditioned by the use of solid fuels, for this reason the analysis includes the external characteristics of the resource (fuel) of residue (ash) and the product (electricity/steam). The energy system used is Termocesar, a Colombian process for generating electricity from carbon. Three functions named thermoeconomic objective function, technology objective function and environmental objective function, are analyzed to establish the best location of the energy The genetic algorithm method is used for the optimization of the system. The results were analyzed for nine combinations of weights and show that for most of the cases the optimum includes coals from the Department of Cesar in Colombia. [ABSTRACT FROM AUTHOR]

The energy efficiency of an electric system depends in great measure of the reactive power compensation that it is carried out. One of the roads more employees are the use of capacitors banks. A good selection of these, presupposes three aspects: the selection of the banks capacity, the compensator type to use, as well as the location in the low voltage system. References of methods that consider the three aspects in a same problem are based on the mathematical programming, but these cannot represent all the effects of the compensation and these based in technical of continuous programming, being this a complex optimization problem of discreet search space. In the paper, we have developed a method with the employment of the genetic algorithms, which facilitates a more exact problem formulation. The method has been programmed in MATLAB, version 7.5 (R2007b), using programming structures of Genetic Algorithm and Direct Search Toolbox.The effectiveness is shown in an example of real application to the low voltage system of a hotel installation of the Cubanacan Company in Camagüey. [ABSTRACT FROM AUTHOR]

This paper presents an heuristics for solving p-median problems. The main idea is the execution of a preprocess routine whose goal is to reduce the number of variables facilitating its computacional resolution. This preprocessing is essentially based in the determination of a maximum distance that enables you to discriminate if two any nodes are served for the same facility. If the distance between these nodes is greater than the maximum distance, then these nodes will not be served for the same facility. As a consequence, variables need to be fixed to zero in order to reduce the size of the problem. [ABSTRACT FROM AUTHOR]

This paper proposes an Ant Colony Optimization method to solve the investment problem for the Transmission Expansion Planning Problem for Electrical Power Systems. Operative problem of Linear Programming is solved trough a High Order Interior Point Method. Moreover, the solution of a Non Linear Interior Point Method is used as a sensitivity index to initialize pheromone matrix used in the Ant Colony Algorithm, where is proposed a method with two stages to obtain a solution. The methodology is tested on the 24 and 6 Bus IEEE systems. [ABSTRACT FROM AUTHOR]

This paper describes an optimization process implemented using Genetic Algorithms. The initial population of the GA is composed of 128 chromosomes with 11 genes per chromosome. The chromosomes of the GA are composed by the length and separations of the elements of the Yagi-Uda antenna; the ranks of this genes where chosen by design standards for such antennas. All genes undergo a process of analysis to assess every one of the antennas of each generation of the GA to assign the fitness of the individuals. In order to verify the obtained results, various tests were made, and among them excel the construction of the optimized Yagi-Uda antenna to measure and verify it electromagnetic characteristics. [ABSTRACT FROM AUTHOR]