3,240 research outputs found

    The Bandwidth minimization problem

    Get PDF
    Mestrado em Métodos Quantitativos para a Decisão Económica e EmpresarialEsta dissertação tem como objetivo comparar o desempenho de duas heurísticas com a resolução de um modelo exato de programação linear inteira na determinação de soluções admissíveis do problema de minimização da largura de banda para matrizes esparsas simétricas. As heurísticas consideradas foram o algoritmo de Cuthill e McKee e o algoritmo Node Centroid com Hill Climbing. As duas heurísticas foram implementadas em VBA e foram avaliadas tendo por base o tempo de execução e a proximidade do valor das soluções admissíveis obtidas ao valor da solução ótima ou minorante. As soluções ótimas e os minorantes para as diversas instâncias consideradas foram obtidos através da execução do código para múltiplas instâncias e através da resolução do problema de Programação Linear Inteira com recurso ao Excel OpenSolver e ao software de otimização CPLEX. Como inputs das heurísticas foram utilizadas matrizes com dimensão entre 4×4 e 5580×5580, diferentes dispersões de elementos não nulos e diferentes pontos de partida.This dissertation intends to compare the performance of two heuristics with the resolution on the exact linear integer program model on the search for admissible solutions of the bandwidth minimization problem for sparse symmetric matrices. The chosen heuristics were the Cuthill and McKee algorithm and the Node Centroid with Hill Climbing algorithm. Both heuristics were implemented in VBA and they were rated taking into consideration the execution time in seconds, the relative proximity of the value obtained to the value of the optimal solution or lower bound. Optimal solutions and lower bounds were obtained through the execution of the code for several instances and trough the resolution of the integer linear problem using the Excel Add-In OpenSolver and the optimization software CPLEX. The inputs for the heuristics were matrices of dimension between 4×4 and 5580×5580, different dispersion of non-null elements and different initialization parameters.info:eu-repo/semantics/publishedVersio

    Data Mining Using the Crossing Minimization Paradigm

    Get PDF
    Our ability and capacity to generate, record and store multi-dimensional, apparently unstructured data is increasing rapidly, while the cost of data storage is going down. The data recorded is not perfect, as noise gets introduced in it from different sources. Some of the basic forms of noise are incorrect recording of values and missing values. The formal study of discovering useful hidden information in the data is called Data Mining. Because of the size, and complexity of the problem, practical data mining problems are best attempted using automatic means. Data Mining can be categorized into two types i.e. supervised learning or classification and unsupervised learning or clustering. Clustering only the records in a database (or data matrix) gives a global view of the data and is called one-way clustering. For a detailed analysis or a local view, biclustering or co-clustering or two-way clustering is required involving the simultaneous clustering of the records and the attributes. In this dissertation, a novel fast and white noise tolerant data mining solution is proposed based on the Crossing Minimization (CM) paradigm; the solution works for one-way as well as two-way clustering for discovering overlapping biclusters. For decades the CM paradigm has traditionally been used for graph drawing and VLSI (Very Large Scale Integration) circuit design for reducing wire length and congestion. The utility of the proposed technique is demonstrated by comparing it with other biclustering techniques using simulated noisy, as well as real data from Agriculture, Biology and other domains. Two other interesting and hard problems also addressed in this dissertation are (i) the Minimum Attribute Subset Selection (MASS) problem and (ii) Bandwidth Minimization (BWM) problem of sparse matrices. The proposed CM technique is demonstrated to provide very convincing results while attempting to solve the said problems using real public domain data. Pakistan is the fourth largest supplier of cotton in the world. An apparent anomaly has been observed during 1989-97 between cotton yield and pesticide consumption in Pakistan showing unexpected periods of negative correlation. By applying the indigenous CM technique for one-way clustering to real Agro-Met data (2001-2002), a possible explanation of the anomaly has been presented in this thesis

    A Two-Level Approach to Large Mixed-Integer Programs with Application to Cogeneration in Energy-Efficient Buildings

    Full text link
    We study a two-stage mixed-integer linear program (MILP) with more than 1 million binary variables in the second stage. We develop a two-level approach by constructing a semi-coarse model (coarsened with respect to variables) and a coarse model (coarsened with respect to both variables and constraints). We coarsen binary variables by selecting a small number of pre-specified daily on/off profiles. We aggregate constraints by partitioning them into groups and summing over each group. With an appropriate choice of coarsened profiles, the semi-coarse model is guaranteed to find a feasible solution of the original problem and hence provides an upper bound on the optimal solution. We show that solving a sequence of coarse models converges to the same upper bound with proven finite steps. This is achieved by adding violated constraints to coarse models until all constraints in the semi-coarse model are satisfied. We demonstrate the effectiveness of our approach in cogeneration for buildings. The coarsened models allow us to obtain good approximate solutions at a fraction of the time required by solving the original problem. Extensive numerical experiments show that the two-level approach scales to large problems that are beyond the capacity of state-of-the-art commercial MILP solvers

    Soft clustering analysis of galaxy morphologies: A worked example with SDSS

    Full text link
    Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover classes automatically. Aims: We briefly discuss the pitfalls of oversimplified classification methods and outline an alternative approach called "clustering analysis". Methods: We categorise different classification methods according to their capabilities. Based on this categorisation, we present a probabilistic classification algorithm that automatically detects the optimal classes preferred by the data. We explore the reliability of this algorithm in systematic tests. Using a small sample of bright galaxies from the SDSS, we demonstrate the performance of this algorithm in practice. We are able to disentangle the problems of classification and parametrisation of galaxy morphologies in this case. Results: We give physical arguments that a probabilistic classification scheme is necessary. The algorithm we present produces reasonable morphological classes and object-to-class assignments without any prior assumptions. Conclusions: There are sophisticated automated classification algorithms that meet all necessary requirements, but a lot of work is still needed on the interpretation of the results.Comment: 18 pages, 19 figures, 2 tables, submitted to A

    Analyzing the Effect of Deceiving Agents in a System of Self-Driving Cars at an intersection - a computational model

    Get PDF
    The creation of protocols for autonomous intersection management is an active research topic with the potential of increasing the capacity of intersections addressing the increasing demand on roads. Most of the proposed protocols assume that all the vehicles involved will behave pro-socially, that is, in a way that improves the outcome of the system over their individual gain. We simulated three different autonomous intersection protocols, two centralized and one decentralized, introducing some egoistic agents that we call deceiving vehicles. Deceiving vehicles may decide to transmit false information while using a protocol if they detect that doing so can result in a lower delay in the intersection. Our simulations show that in two of the protocols, it is possible for a deceiving vehicle to experience lower delay times compared to its non-deceiving counterparts. Additionally, as more deceiving vehicles enter the system the overall capacity of an intersection can be reduced, increasing delays for non-deceiving vehicles which creates an incentive for more vehicles to deceive. We pose that, given that vehicles have an incentive to deceive, autonomous intersection protocol's authors need to consider deceiving vehicles in their design and include measures to prevent them, thus avoiding the performance degradation they produce.La creación de protocolos de manejo autónomo de intersecciones es un tema de investigación activo que tiene el potencial de aumentar la capacidad de las intersecciones aportando a la solución del problema del creciente aumento en la demanda en las vías. La mayoría de los protocolos propuestos asumen que todos los vehículos se comportan de manera prosocial, es decir, que actúan de una manera que beneficia al sistema sobre su propio beneficio. Nosotros simulamos tres protocolos de intersección autónomos, dos centralizados y uno descentralizado, introduciendo algunos agentes egoístas que llamamos vehículos engañosos. Los vehículos engañosos pueden decidir transmitir información falsa cuando usan un protocolo si detectan que hacerlo puede resultar una demora menor en la intersección. Nuestras simulaciones muestran que, en dos de los protocolos, es posible que los vehículos engañosos experimenten demoras menores frente a sus contrapartes no-engañosos. Asimismo, conforme más vehículos engañosos son introducidos en el sistema, la capacidad total de la intersección se ve reducida, aumentando las demoras para los vehículos que no son engañosos lo que genera un incentivo para que más vehículos sean engañosos. Proponemos que, dado que los vehículos tienen incentivos para engañar, los autores de protocolos de intersecciones autónomas deben considerar los vehículos engañosos en su diseño e incluir medida para prevenirlos, evitando así la degradación en rendimiento que producen.MaestríaSistemas Inteligente

    Complementarity constraints and induced innovation: Some evidence from the first IT regime

    Get PDF
    Technological search is often depicted to be random. This paper takes a different view and analyses how innovative recombinant search is triggered, how it is done and what initial conditions influence the final design of technological artefacts. We argue that complementarities (non-separabilities) play an important role as focusing devices guiding the search for new combinations. Our analysis takes the perspective of technology adopters and not that of inventors or innovators of new products. We illustrate the process of decomposition and re-composition under the presence of binding complementarity constraints with a historical case study on the establishment of the First IT Regime at the turn of the 19th century.Technological regimes, systemic innovation, adoption of technologies, complexity,information technology 1870-1930
    corecore