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Introduction-- In this work large areas with sources of pollution emissions are considered, and in most cases they go far beyond industrial areas. Using modeling, monitoring or forecasting in the optimization algorithms, the pollution propagation parameters can be analyzed and ajusted with the negative impact of industrial areas. Objective-- The objective is to optimize the proposed model using three subsets (reformed without restrictions, with restrictions and not reformed) of pollution sources and their validation. Methodology-- For the minimization, the Nelder-Mead procedure of local classical optimization was used, which by changing the pitch can find the extremes quite accurate and, in addition, serves for multi-parameter optimization. Results-- The results obtained allow: the choice of industrial zones size, the location of industries with conditional sources and without restrictions, optimization limits according to the number of iterations or according to the integral of the emissions and valuation of the economic consequences of the solution. Conclusions-- The mathematical model and algorithm are quite simple in their application and are open for more complexity. [ABSTRACT FROM AUTHOR]

Introduction: Cylindrical gear transmissions design continues to be a great importance topic. With the increasing development of computational methods, many authors have worked on such transmissions optimization with increasing their load capacity and / or extending their useful life as fundamental objective. Objective: To evaluate the influence of the correction factor over contact stresses in tooth profile, considering the geometric constraints and to determine correction factor for minimum contact stresses. Materials and Methods: By formulating the Hertz Budynas - Nisbett theory for two cylinders in contact, the optimization problem is formulated with restrictions that are solved by different optimization methods, a solution method developed by the authors is evaluated. Results and Discussion: The proposed method is validated by the comparison of obtained correction factors, with its recommended by the KISSSoft-v2014 design program factors, evaluated for the standards (AGMA, 2004; ISO 6336-2, 2006) implemented by the authors Conclusions: Correction value factor is obtained, achieving a better distribution of contact stresses on tooth in work area. The numerical method presented, obtains the same results than classical optimization methods, validating its use in problem solution. [ABSTRACT FROM AUTHOR]

In this report the results of the application of genetic algorithms and PSO (Particle Swarm Optimization) are presented to optimize a problem of distributed generation (DG) of power that must meet certain restrictions. For the implementation of the genetic algorithm toolbox of Matlab it is used and implemented fraction varying parameters such as mutation, population etc. This for comparison with the function fmincon already implemented within the Matlab environment and draw conclusions regarding convergence and error rate between data. The PSO algorithm was implemented taking into account stochastic processes based on luck, defining him intrinsic properties, such as population size, inertia factor etc. [ABSTRACT FROM AUTHOR]

Many problems of optimization are characterized by the flexibility to establish the utility among the functions objectives. Experimental strategy plays a very important part for generating theses functions. This specific strategy has also been applied in an important way to reduce costs when desiring quality and its continuous improvement in processes and products. It is common to find many industrial applications with several responses whose purpose is to reach the global level of quality of a product. Therefore it is necessary to simultaneously optimize in a simultaneous the responses that the researcher desires. In essence, the problem of optimization of various responses involves the selection of a set of conditions or independent variables such that give a product or some convenient service an ideal result. The wish is to select the levels of independent variables that optimize all the responses at the same time. Two procedures will be displayed here in order to build a function that represents a combination of the objectives of the individual responses. The first method is a model of optimization multiplicativo and the second additive. These will be applied to two cases of study which will be carried out in the industry for the purpose of pointing out the processes of continuous improvement and the decrease in costs. The simultaneous optimization, using these two procedures, will be illustrated by graphical means. This will allow a generation of several scenarios showing possible optimum solutions. In these examples it was observed that both methods produce similar results when generating the optimum one, however when comparing them in a global way by means of the loss function a slight difference it exists among them. [ABSTRACT FROM AUTHOR]

In this paper we analyze the yields of a queue management policy in a commuter of a network, which receives two classes of traffic with different requisites of quality with respect to retards and losses. We prove how the state probabilities of the system can be obtained recursively and from the mean retards of arrivals of both traffic classes as well as their loss rates. These quantities are linked with the calculus of the yields of the system by means of the objective function that represents a weighting of the associated cost produced by the retards produced by the priority traffic (in real time) and the losses originated by the non prioritary traffic (in non real time). [ABSTRACT FROM AUTHOR]