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The Ball Mill Abrasion Test (BMAT) is a laboratory experiment used to measure the resistance of materials under high-stress abrasion conditions. This test, however, has yet to be standardized. In this work, statistical theory determines the optimal number of spheres per material to be included in BMAT. This theory and the optimization method presented in this paper show that the optimal number of spheres for the usual experimental conditions is six. Finally, it is shown that if the optimization process is extended over a broader range of experimental conditions, the optimum number of spheres per material is also six. [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]

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 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]

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]

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]

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]

This paper presents an effective approach to simultaneous solution of capacitor placement and feeder reconfiguration for power-energy loss cost minimization and voltage profile enhancement in radial distribution systems. Considering a time variation load, an optimization method using a genetic algorithm is proposed to determine the optimal location and size of fixed and switchable capacitors, as well as the open/closed states of the sectionalizing and tie switches. Reduction of overall power and energy losses and capacitor costs are involved in problem formulation. The proposed approach is demonstrated using example systems from the literature and results show that taken into account both capacitor placement and feeder reconfiguration simultaneously can generate around 10% more energy and peak loss reduction than considering them separately. Simulations results are presented for a 16 bus IEEE system and for a 733 bus practical distribution network. [ABSTRACT FROM AUTHOR]

ACO is a metaheuristic inspired in the behavior of natural ant colonies to solve combinatorial optimization problems, based on simple agents that work cooperatively communicating by artificial pheromone trails. In this paper a model to solve the municipal waste collection problem by containers is presented, which applies a concept of partial collection sequences that must be joined to minimize the total collection distance. The problem to join the partial collection sequences is represented as a TSP, which is solved by an ACO algorithm. Based on the literature, algorithm parameters are experimentally calibrated and range of variations that represents good average solutions are recommended. The model is applied to a waste collection sector of the San Pedro de la Paz commune in Chile, obtaining recollection routes with less total distance with respect to the actual route utilized and to the solution obtained by a previously developed approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel algorithm to reconfigure an electric power distribution network (EPDN) minimizing its non-supplied energy (NSE). The EPDN is modeled using graph theory and the NSE is recursively formulated in terms of the reliability parameters of the EPDN. Based on this mathematical model, we transform the original optimization problem into the graph theory problem of finding the minimum spanning tree (MST) of a given graph, which models the EPDN. The distance metric employed by the searching algorithm is the NSE. In order to efficiently find the MST, Prim's algorithm is employed due to is greedy search behavior. In addition, a backtracking algorithm is used to check the MST obtained. The backtracking algorithm analyzes all the candidate topologies that were randomly discarded during the decision process. The performance of the optimization algorithm is evaluated by using testing systems and two actual EPDNs. [ABSTRACT FROM AUTHOR]