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Recent Advances in Global Optimization
Christodoulos A. Floudas, Panos M. Pardalos
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Naturwissenschaften, Medizin, Informatik, Technik / Mathematik
Beschreibung
This book will present the papers delivered at the first U.S. conference devoted exclusively to global optimization and will thus provide valuable insights into the significant research on the topic that has been emerging during recent years. Held at Princeton University in May 1991, the conference brought together an interdisciplinary group of the most active developers of algorithms for global optimization in order to focus the attention of the mathematical programming community on the unsolved problems and diverse applications of this field. The main subjects addressed at the conference were advances in deterministic and stochastic methods for global optimization, parallel algorithms for global optimization problems, and applications of global optimization. Although global optimization is primarily a mathematical problem, it is relevant to several other disciplines, including computer science, applied mathematics, physical chemistry, molecular biology, statistics, physics, engineering, operations research, communication theory, and economics. Global optimization problems originate from a wide variety of mathematical models of real-world systems. Some of its applications are allocation and location problems and VLSI and data-base design problems.
Originally published in 1991.
The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
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Upper and lower bounds, Exponential function, Lipschitz continuity, Ranking (information retrieval), Variable (computer science), Search algorithm, Summation, Covering problems, Lagrange multiplier, Optimal design, Computation, Local optimum, Time complexity, Homotopy, Iteration, Search problem, Linear complementarity problem, Approximation algorithm, Extreme point, Rate of convergence, Linear programming, Optimal control, Simplex algorithm, Conjugate gradient method, Maxima and minima, NP-hardness, Root-finding algorithm, Dynamic programming, Local search (optimization), Central limit theorem, Constrained optimization, Special case, Result, Robustness (computer science), Priority queue, Complex plane, Global optimization, Newton's method, Algorithmic efficiency, Direction vector, Linearization, Big O notation, Trust region, Order of accuracy, Speedup, Deterministic global optimization, Polynomial, Stochastic programming, Algorithm, Loss function, Function problem, Decision problem, Computational complexity theory, Pareto efficiency, Iterative method, Calculation, Exponential growth, Quadratic function, Accuracy and precision, Mathematical optimization, Equation, Maximum likelihood estimation, Bifurcation theory, Portfolio optimization, Quadratic programming, Feasible region, Duality (optimization), Optimization problem, Theorem, Combinatorial optimization