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Author : Roselyn Mansa Abbiw-Jackson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (652 download)
Download or read book Discrete Optimization Models in Data Visualization written by Roselyn Mansa Abbiw-Jackson and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : E. Boros
Publisher : Elsevier
ISBN 13 : 008093028X
Total Pages : 587 pages
Book Rating : 4.0/5 (89 download)
Download or read book Discrete Optimization written by E. Boros and published by Elsevier. This book was released on 2003-03-19 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most frequently occurring types of optimization problems involves decision variables which have to take integer values. From a practical point of view, such problems occur in countless areas of management, engineering, administration, etc., and include such problems as location of plants or warehouses, scheduling of aircraft, cutting raw materials to prescribed dimensions, design of computer chips, increasing reliability or capacity of networks, etc. This is the class of problems known in the professional literature as "discrete optimization" problems. While these problems are of enormous applicability, they present many challenges from a computational point of view. This volume is an update on the impressive progress achieved by mathematicians, operations researchers, and computer scientists in solving discrete optimization problems of very large sizes. The surveys in this volume present a comprehensive overview of the state of the art in discrete optimization and are written by the most prominent researchers from all over the world. This volume describes the tremendous progress in discrete optimization achieved in the last 20 years since the publication of Discrete Optimization '77, Annals of Discrete Mathematics, volumes 4 and 5, 1979 (Elsevier). It contains surveys of the state of the art written by the most prominent researchers in the field from all over the world, and covers topics like neighborhood search techniques, lift and project for mixed 0-1 programming, pseudo-Boolean optimization, scheduling and assignment problems, production planning, location, bin packing, cutting planes, vehicle routing, and applications to graph theory, mechanics, chip design, etc. Key features: • state of the art surveys • comprehensiveness • prominent authors • theoretical, computational and applied aspects. This book is a reprint of Discrete Applied Mathematics Volume 23, Numbers 1-3
Author : Sebastian Volke
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (115 download)
Download or read book Towards Visualization of Discrete Optimization Problems and Search Algorithms written by Sebastian Volke and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Qie He
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (88 download)
Download or read book Topics in Discrete Optimization written by Qie He and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation we examine several discrete optimization problems through the perspectives of modeling, complexity and algorithms. We first provide a probabilistic comparison of split and type 1 triangle cuts for mixed-integer programs with two rows and two integer variables in terms of cut coefficients and volume cutoff. Under a specific probabilistic model of the problem parameters, we show that for the above measure, the probability that a split cut is better than a type 1 triangle cut is higher than the probability that a type 1 triangle cut is better than a split cut. The analysis also suggests some guidelines on when type 1 triangle cuts are likely to be more effective than split cuts and vice versa. We next study a minimum concave cost network flow problem over a grid network. We give a polytime algorithm to solve this problem when the number of echelons is fixed. We show that the problem is NP-hard when the number of echelons is an input parameter. We also extend our result to grid networks with backward and upward arcs. Our result unifies the complexity results for several models in production planning and green recycling including the lot-sizing model, and gives the first polytime algorithm for some problems whose complexities were not known before. Finally, we examine how much complexity randomness will bring to a simple combinatorial optimization problem. We study a problem called the sell or hold problem (SHP). SHP is to sell k out of n indivisible assets over two stages, with known first-stage prices and random second-stage prices, to maximize the total expected revenue. Although the deterministic version of SHP is trivial to solve, we show that SHP is NP-hard when the second-stage prices are realized as a finite set of scenarios. We show that SHP is polynomially solvable when the number of scenarios in the second stage is constant. A max{1/2,k/n}-approximation algorithm is presented for the scenario-based SHP.
Author : Koji Koyamada
Publisher : World Scientific
ISBN 13 : 981128363X
Total Pages : 230 pages
Book Rating : 4.8/5 (112 download)
Download or read book Analysis And Visualization Of Discrete Data Using Neural Networks written by Koji Koyamada and published by World Scientific. This book was released on 2024-01-22 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a comprehensive step-by-step guide on data analysis and statistical analysis. It covers fundamental operations in Excel, such as table components, formula bar, and ribbon, and introduces visualization techniques and PDE derivation using Excel. It also provides an overview of Google Colab, including code and text cells, and explores visualization and deep learning applications.Key features of the book include topics like statistical analysis, regression analysis, optimization, correlation analysis, and neural networks. It adopts a practical approach by providing examples and step-by-step instructions for learners to apply the techniques to real-world problems.The book also highlights the strengths and features of both Excel and Google Colab, allowing learners to leverage the capabilities of each platform. The clear explanations of concepts, visual aids, and code snippets aid comprehension help learners understand the principles of data analysis and statistical analysis. Overall, this book serves as a valuable resource for professionals, researchers, and students seeking to develop skills in data analysis, regression statistics, optimization, and advanced modeling techniques using Excel, Colab, and neural networks.
Author :
Publisher : Elsevier
ISBN 13 : 0080867677
Total Pages : 461 pages
Book Rating : 4.0/5 (88 download)
Download or read book Discrete Optimization I written by and published by Elsevier. This book was released on 2000-04-01 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete Optimization I
Author : Adam Kasperski
Publisher : Springer Science & Business Media
ISBN 13 : 3540784837
Total Pages : 225 pages
Book Rating : 4.5/5 (47 download)
Download or read book Discrete Optimization with Interval Data written by Adam Kasperski and published by Springer Science & Business Media. This book was released on 2008-06-04 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations research often solves deterministic optimization problems based on elegantand conciserepresentationswhereall parametersarepreciselyknown. In the face of uncertainty, probability theory is the traditional tool to be appealed for, and stochastic optimization is actually a signi?cant sub-area in operations research. However, the systematic use of prescribed probability distributions so as to cope with imperfect data is partially unsatisfactory. First, going from a deterministic to a stochastic formulation, a problem may becomeintractable. Agoodexampleiswhengoingfromdeterministictostoch- tic scheduling problems like PERT. From the inception of the PERT method in the 1950’s, it was acknowledged that data concerning activity duration times is generally not perfectly known and the study of stochastic PERT was launched quite early. Even if the power of today’s computers enables the stochastic PERT to be addressed to a large extent, still its solutions often require simplifying assumptions of some kind. Another di?culty is that stochastic optimization problems produce solutions in the average. For instance, the criterion to be maximized is more often than not expected utility. This is not always a meaningful strategy. In the case when the underlying process is not repeated a lot of times, let alone being one-shot, it is not clear if this criterion is realistic, in particular if probability distributions are subjective. Expected utility was proposed as a rational criterion from ?rst principles by Savage. In his view, the subjective probability distribution was - sically an artefact useful to implement a certain ordering of solutions.
Author : B.K. Tripathy
Publisher : CRC Press
ISBN 13 : 1000438317
Total Pages : 174 pages
Book Rating : 4.0/5 (4 download)
Download or read book Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization written by B.K. Tripathy and published by CRC Press. This book was released on 2021-09-01 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data. Underlying mathematical concepts, derivations, and proofs with logical explanations for these algorithms are discussed, including strengths and limitations. The book highlights important use cases of these algorithms and provides examples along with visualizations. Comparative study of the algorithms is presented to give a clear idea on selecting the best suitable algorithm for a given dataset for efficient dimensionality reduction and data visualization. FEATURES Demonstrates how unsupervised learning approaches can be used for dimensionality reduction Neatly explains algorithms with a focus on the fundamentals and underlying mathematical concepts Describes the comparative study of the algorithms and discusses when and where each algorithm is best suitable for use Provides use cases, illustrative examples, and visualizations of each algorithm Helps visualize and create compact representations of high dimensional and intricate data for various real-world applications and data analysis This book is aimed at professionals, graduate students, and researchers in Computer Science and Engineering, Data Science, Machine Learning, Computer Vision, Data Mining, Deep Learning, Sensor Data Filtering, Feature Extraction for Control Systems, and Medical Instruments Input Extraction.
Author : Panos M. Pardalos
Publisher : American Mathematical Soc.
ISBN 13 : 0821832484
Total Pages : 194 pages
Book Rating : 4.8/5 (218 download)
Download or read book Novel Approaches to Hard Discrete Optimization written by Panos M. Pardalos and published by American Mathematical Soc.. This book was released on 2003 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade, many novel approaches have been considered for dealing with computationally difficult discrete optimization problems. Such approaches include interior point methods, semidefinite programming techniques, and global optimization. More efficient computational algorithms have been developed and larger problem instances of hard discrete problems have been solved. This progress is due in part to these novel approaches, but also to new computing facilities and massive parallelism. This volume contains the papers presented at the workshop on ``Novel Approaches to Hard Discrete Optimization''. The articles cover a spectrum of issues regarding computationally hard discrete problems.
Author : Gautam M. Appa
Publisher : Springer Science & Business Media
ISBN 13 : 0387329420
Total Pages : 443 pages
Book Rating : 4.3/5 (873 download)
Download or read book Handbook on Modelling for Discrete Optimization written by Gautam M. Appa and published by Springer Science & Business Media. This book was released on 2006-08-18 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to demonstrate and detail the pervasive nature of Discrete Optimization. The handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It is done with an academic treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research. The book utilizes the tools of mathematical modeling, optimization, and integer programming to solve a broad range of modern problems.
Author : Hesam Shams
Publisher :
ISBN 13 :
Total Pages : 108 pages
Book Rating : 4.:/5 (119 download)
Download or read book Learning Models for Discrete Optimization written by Hesam Shams and published by . This book was released on 2018 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a class of optimization approaches that incorporate machine learning models into the algorithm structure. Our focus is on the algorithms that can learn the patterns in the search space in order to boost computational performance. The idea is to design optimization techniques that allow for computationally efficient tuning a priori. The final objective of this work is to provide efficient solvers that can be tuned for optimal performance in serial and parallel environments.This dissertation provides a novel machine learning model based on logistic regression and describes an implementation for scheduling problems. We incorporate the proposed learning model into a well-known optimization algorithm, tabu search, and demonstrate the potential of the underlying ideas. The dissertation also establishes a new framework for comparing optimization algorithms. This framework provides a comparison of algorithms that is statistically meaningful and intuitive. Using this framework, we demonstrate that the inclusion of the logistic regression model into the tabu search method provides significant boost of its performance. Finally, we study the parallel implementation of the algorithm and evaluate the algorithm performance when more connections between threads exist.
Author : E. Boros
Publisher : JAI Press
ISBN 13 : 9780444512956
Total Pages : 0 pages
Book Rating : 4.5/5 (129 download)
Download or read book Discrete Optimization written by E. Boros and published by JAI Press. This book was released on 2003-03-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most frequently occurring types of optimization problems involves decision variables which have to take integer values. From a practical point of view, such problems occur in countless areas of management, engineering, administration, etc., and include such problems as location of plants or warehouses, scheduling of aircraft, cutting raw materials to prescribed dimensions, design of computer chips, increasing reliability or capacity of networks, etc. This is the class of problems known in the professional literature as "discrete optimization" problems. While these problems are of enormous applicability, they present many challenges from a computational point of view. This volume is an update on the impressive progress achieved by mathematicians, operations researchers, and computer scientists in solving discrete optimization problems of very large sizes. The surveys in this volume present a comprehensive overview of the state of the art in discrete optimization and are written by the most prominent researchers from all over the world. This volume describes the tremendous progress in discrete optimization achieved in the last 20 years since the publication of Discrete Optimization '77, Annals of Discrete Mathematics, volumes 4 and 5, 1979 (Elsevier). It contains surveys of the state of the art written by the most prominent researchers in the field from all over the world, and covers topics like neighborhood search techniques, lift and project for mixed 0-1 programming, pseudo-Boolean optimization, scheduling and assignment problems, production planning, location, bin packing, cutting planes, vehicle routing, and applications to graph theory, mechanics, chip design, etc. Key features: . state of the art surveys . comprehensiveness . prominent authors . theoretical, computational and applied aspects. This book is a reprint of Discrete Applied Mathematics Volume 23, Numbers 1-3
Author : R. Gary Parker
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (162 download)
Download or read book Discrete Optimization written by R. Gary Parker and published by . This book was released on 1983 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 244 pages
Book Rating : 4.:/5 (939 download)
Download or read book Discrete Optimization in Early Vision written by and published by . This book was released on 2012 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bogdan Savchynskyy
Publisher :
ISBN 13 : 9781680836387
Total Pages : 286 pages
Book Rating : 4.8/5 (363 download)
Download or read book Discrete Graphical Models written by Bogdan Savchynskyy and published by . This book was released on 2019-12-10 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is about discrete energy minimization for discrete graphical models. It considers graphical models, or, more precisely, maximum a posteriori inference for graphical models, purely as a combinatorial optimization problem.
Author : Michael Breuß
Publisher : Springer Science & Business Media
ISBN 13 : 3642341411
Total Pages : 510 pages
Book Rating : 4.6/5 (423 download)
Download or read book Innovations for Shape Analysis written by Michael Breuß and published by Springer Science & Business Media. This book was released on 2013-04-04 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of 'shape' is at the heart of image processing and computer vision, yet researchers still have some way to go to replicate the human brain's ability to extrapolate meaning from the most basic of outlines. This volume reflects the advances of the last decade, which have also opened up tough new challenges in image processing. Today's applications require flexible models as well as efficient, mathematically justified algorithms that allow data processing within an acceptable timeframe. Examining important topics in continuous-scale and discrete modeling, as well as in modern algorithms, the book is the product of a key seminar focused on innovations in the field. It is a thorough introduction to the latest technology, especially given the tutorial style of a number of chapters. It also succeeds in identifying promising avenues for future research. The topics covered include mathematical morphology, skeletonization, statistical shape modeling, continuous-scale shape models such as partial differential equations and the theory of discrete shape descriptors. Some authors highlight new areas of enquiry such as partite skeletons, multi-component shapes, deformable shape models, and the use of distance fields. Combining the latest theoretical analysis with cutting-edge applications, this book will attract both academics and engineers.
Author : Advanced Research Institute on Discrete Optimization and Systems Applications
Publisher :
ISBN 13 :
Total Pages : 299 pages
Book Rating : 4.:/5 (658 download)
Download or read book Discrete Optimization I written by Advanced Research Institute on Discrete Optimization and Systems Applications and published by . This book was released on 1979 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt:
