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This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.
Mathematics. --- Computer science --- Algorithms. --- Computer software. --- Mathematical optimization. --- Continuous Optimization. --- Mathematical Software. --- Math Applications in Computer Science. --- Linear programming. --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Math --- Science --- Mathematics --- Production scheduling --- Programming (Mathematics) --- Computer science. --- Algorism --- Algebra --- Arithmetic --- Informatics --- Software, Computer --- Computer systems --- Foundations --- Programación lineal --- Computer science—Mathematics. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematical Applications in Computer Science.
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Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France).
Python (Computer program language) --- Scripting languages (Computer science) --- Operations research. --- Software engineering. --- Computer software. --- Operations Research, Management Science. --- Operations Research/Decision Theory. --- Software Engineering/Programming and Operating Systems. --- Mathematical Software. --- Mathematical Applications in Computer Science. --- Software, Computer --- Computer systems --- Computer software engineering --- Engineering --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Management science. --- Decision making. --- Computer science—Mathematics. --- Computer mathematics. --- Computer mathematics --- Electronic data processing --- Mathematics --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Quantitative business analysis --- Operations research --- Statistical decision --- Decision making --- Operations Research, Management Science . --- Operations Research and Decision Theory. --- Software Engineering.
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GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book, examples and source codes illustrate every concept so that readers can immediately apply them to their own development. Provides in-depth, comprehensive coverage of GPUs with MATLAB, including the parallel computing toolbox and built-in features for other MATLAB toolboxes Explains how to accelerate computationally heavy applications in MATLAB without the need to re-write them in another language Presents case studies illustrating key concepts across multiple fields Includes source code, sample datasets, and lecture slides
Graphics processing units --- Parallel processing (Electronic computers) --- Programming. --- MATLAB.
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This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system’s life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering ‘good’ and ‘bad’ practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike. “A book on real case studies in Decision Support Systems is a much-needed publication in an area where most literature has been dedicated to theory, underestimating the empirical dimension of decision-making support. I am very glad to see this book appearing. It really fills a gap”. Professor Alexis Tsoukiàs, Director of LAMSADE, CNRS - LAMSADE, Université Paris Dauphine, France. “This book is informative, interesting, and inter-disciplinary. It exemplifies how Decision Support Systems can transform, influence, and impact real-world practices”. Professor Shaofeng Liu, Plymouth Graduate School of Management & Plymouth Business School, Plymouth University, UK. “A very attractive book that undoubtedly augments our understanding of Decision Support Systems and their myriad of applications. I would like to offer my congratulations to the authors and recommend the book to all potential readers". Professor José María Moreno-Jimenez, Faculty of Economics and Business, University of Zaragoza, Spain, and President of the International Association of Applied Economics Asepelt.
IT in Business. --- Decision making. --- Decision support systems. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Decision making --- Management information systems --- Telematics --- Information technology. --- Operations research. --- Software engineering. --- Information Systems Applications (incl. Internet). --- Operations Research/Decision Theory. --- Software Engineering. --- Computer software engineering --- Engineering --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- IT (Information technology) --- Technology --- Information superhighway --- Knowledge management --- Application software. --- Business—Data processing. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Business information services. --- Computer and Information Systems Applications. --- Operations Research and Decision Theory. --- Business --- Business enterprises --- Information services
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