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Introduction This paper presents a proposal to apply the meta-heuristic Optimization Based on Variable Meshes (VMO) to the discreet problem of the Traveler Seller (TSP); This model explores the search space to Objective from a population of solutions called mesh that expands and contracts in order to find good quality solutions. In this context, the expansion operator is modified in such a way that it is applicable in a discrete domain, making combinations among the solutions in order to obtain new nodes. Another element that is modified is the clearing operator, which is responsible for maintaining the diversity of the mesh in each interaction. Methodology. A study of VMO model parameters is summarized in this paper, using a set of TSP instances with different characteristics; In addition, it can be observed that the proposal of this work obtains competitive results when compared with other international reference algorithms mentioned in the state of the art. The work is structured as follows: Section 1 describes the fundamental aspects of the TSP study problem. Then, in the second, the general functioning of VMO is explained, in the third one, each of the expansion and contraction operators is defined for the study problem. Later in the fourth section a study of the parameters of the proposal and an experimental comparative analysis with the results obtained with other algorithms mentioned in the state of the art is made. Conclusions Other operators of generation of new nodes were applied in the expansion process, where a combination of solutions is made in order to comply with the restrictions imposed by the problem. [ABSTRACT FROM AUTHOR]

This paper presents the procedure of tuning and simulation of an adaptive predictive control strategy to control the longitudinal and latero-directional movements of a unmanned aerial vehicle (UAV), using the Matlab ® - Simulink® platform. Uses the mathematical model of a UAV which are initially performed simulations of the system in open loop, identification is carried on online, and predictive control and PID controllers algorithms are implemented with the parameters obtained, to control the angle of pitch, roll and yaw. Control strategies used presented a good performance and manage to stabilize the aircraft properly. Finally, they are presented and analyzed the results of the performance of the system with predictive control and PID control using metrics of the integral of the error and of the work of the manipulated variable. [ABSTRACT FROM AUTHOR]

The placement of convex objects in the plane, specially rectangular objects has been studied extensively in the literature and its applications to VLSI designs, the steel industry (stock cutting). The placement of non convex objects and its application in many design and textile industries, specially the textile industry has been less studied. Mathematical Approaches determining and adequate solution of such problems include linear programming and the newest genetic algorithms. In this paper we consider a particular industrial problem, the design of printing sheets for decorative porcelain. These objects permit inclusions and other geometric situations which do not appear in the case of convex objects. In this paper we proof results related with this problem for different algorithms: a heuristic algorithm, simulated annealing algorithm and a genetic algorithm. [ABSTRACT FROM AUTHOR]

In this paper three new algorithms for the random generation of permutations of degree n are shown, two of them for the Symmetric group Sn and one for the Alternating group An, in such a way, that they are mainly carried out by means of the operation of additions mod no mod i, i = n.2. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to reduce energy losses in primary distribution networks, considering a combined algorithm which involves the optimal reconfiguration of the system and phase balance. The mathematical model is nonlinear mixed integer, which takes into account the investment and operating costs of the network, subject to a set of technical constraints imposed by the system. To solve the problem of reconfiguration and phase balance algorithms are used Simulated Annealing and Ant Colony, respectively. The algorithm is tested on IEEE 37 node feeder. [ABSTRACT FROM AUTHOR]

A model for collision detection based on double hierarchical spherical representation is proposed in this paper: an outer spherical representation for detecting no-intersections and an inner spherical representation in order to improve the performance of the collision detector. The algorithm has been implemented. Several tests were conducted with convex polyhedral and the performance of the algorithm was evaluated in terms of the collision between inner spheres. The experimental results show that outer spheres have been useful to determine lack of intersection, whereas inner spheres are more efficient for detecting existence of intersection and for speeding up the process of detecting collision. Using inner spheres improve the general performance because it reduces the number of intersection tests between the faces of the polyhedral. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for solving secondary distribution systems planning problem as a mixed integer linear programming problem (MILP). The algorithm takes into account several design issues such as the capacity and location of distribution transformers and secondary feeders. Variable costs of secondary feeders are also considered. The problem is solved using branch and bound algorithm. Numerical results show that the mathematical model and the solution technique are effective for this kind of problems. [ABSTRACT FROM AUTHOR]

One of the difficulties students from basic courses often show in learning probability and statistics at the university is understanding how the continuous normal probability distribution approximates the discrete binomial probability distribution. In this paper a didactic proposal is presented consisting in two algorithms, very easy to use, developed with software R which is completely free. These algorithms aim to introduce students in basic concepts of normal approximation to the binomial distribution by means of graphical representations and tables. They allow an active participation of student in the learning process. [ABSTRACT FROM AUTHOR]

This paper presents the application of an evolutionary algorithm using Matlab to obtain the optimum main angles of the cutting geometry of a machining tool. The optimization method considered the non linear model of Kaldor and Venuvinod. Different algorithm configurations were tested using data obtained from the literature. Several simulations were carried out to validate the performance of the algorithm and to show the usefulness of the method employed. It is concluded that that the proposed approach shows to be stable and coherent in the results for the cases studied. [ABSTRACT FROM AUTHOR]

In this paper we present an algorithm of binary classification based on Support Vector Machines. It is combined with a modified Boosting algorithm. It run faster than the original SVM algorithm with a similar generalization error and equal complexity model but it has more compact representation. [ABSTRACT FROM AUTHOR]

In many applications the importance of evaluating the consensus is growing. This is particularly important in many biomedical studies where the role of the experts is crucial. That is the case when the efficacy of treatments, the classification of patients, the quality of the biosphere in certain places or tests is studied. This paper is devoted to the development of a review of the κ index, indexes deduced or deducible from it as particular cases under certain models. Properties of them for different models are discussed. The models support parametric inferences or provide a statistical frame for analyzing the consensus in the classification among experts. Different examples are developed with illustrating purposes. [ABSTRACT FROM AUTHOR]

In this paper, we compare, from a theoretical and a practical viewpoint, two settings of a certain tax-programming problem and the algorithms proposed for solving it. This problem may be modeled as a parametric quadratic-programming problem having lower and upper bounds on the variables. The objective function is a quadratic function whose Hessian matrix is diagonal and positive. A term is added that penalizes not to achieving a certain goal. This penalization can be formulated either as an absolute or as a quadratic deviation. [ABSTRACT FROM AUTHOR]