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In an era dominated by mathematical and statistical models, this book unravels the profound significance of these tools in decoding uncertainties within numerical, observational, and calculation-based data.
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Discusses machine learning models and their optimization in mathematical modeling. Covers important topics such as linear integer... Læs mere
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This book presents recent theoretical findings on Sliding Mode Control (SMC) issues for various classes of complex nonlinear systems based on... Læs mere
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This text covers the basic theory and computation for mathematical modeling in linear programming.
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This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits for data and information science and technology.
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R.E. Miller: Parallel program schemata.- D.E. Muller: Theory of automata.- R. Karp: Computational complexity of combinatorial and graph-theoretic problems.
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Presenting an overview of the field, this volume discusses computational aspects of queueing networks and their applications. The text examines both analytical... Læs mere
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The papers published in this volume focus on some of the most recent devel- ments in complementarity theory, variational principles, stability theory of fu- tional equations, nonsmooth optimization, and various other important topics of nonlinear analysis and optimization.
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Metaheuristics support managers in decision-making with robust tools that provide high-quality solutions to important applications... Læs mere
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With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, the primal-dual simplex method, the path-following interior-point method, and and the homogeneous self-dual method.
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This book provides a handy, unified introduction to the theory of compact extended formulations of exponential-size integer linear programming (ILP) models.