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.
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Key Phrases - Statistically Improbable Phrases (SIPs):
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vertical block matrix, cis yis, reactor reload design, complementary feasible solution, revised master problem, initial solution technique, graph minima, topographical global optimization, dogleg strategy, concave quadratic programs, branched solutions, isovalue contour, convex maximization problem, topography graph, affine homotopy, reverse convex constraint, underestimating function, box queue, variables yis, pending nodes, linear lower bounds, midpoint test, linear fractional functions, interval newton method, composite objective function Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Computer Science, Management Science, Modified Frank-Wolfe Algorithm, Monte Carlo, Research Report, Academic Press, New Jersey, Technical Report, Academy of Sciences, Applied Mathematics, Lecture Notes, Naval Research Logistics Quarterly, Normalized Powers, Rinnooy Kan, Beaver Valley, Englewood Cliffs, The Netherlands, Acta Mathematicae Applicatae Sinica, Algorithm Param, Markov Decision Process, Tokyo Institute of Technology, Water Resources Research, Analyse Phase, Constructed Objective Function New!
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vertical block matrix, cis yis, reactor reload design, complementary feasible solution, revised master problem, initial solution technique, graph minima, topographical global optimization, dogleg strategy, concave quadratic programs, branched solutions, isovalue contour, convex maximization problem, topography graph, affine homotopy, reverse convex constraint, underestimating function, box queue, variables yis, pending nodes, linear lower bounds, midpoint test, linear fractional functions, interval newton method, composite objective function Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Computer Science, Management Science, Modified Frank-Wolfe Algorithm, Monte Carlo, Research Report, Academic Press, New Jersey, Technical Report, Academy of Sciences, Applied Mathematics, Lecture Notes, Naval Research Logistics Quarterly, Normalized Powers, Rinnooy Kan, Beaver Valley, Englewood Cliffs, The Netherlands, Acta Mathematicae Applicatae Sinica, Algorithm Param, Markov Decision Process, Tokyo Institute of Technology, Water Resources Research, Analyse Phase, Constructed Objective Function New!
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Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
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43
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- Complexity in Numerical Optimization by Panos M. Pardalos on 4 pages
- Handbook of Global Optimization Volume 2 (Nonconvex Optimization and Its Applications (closed)) by Panos M. Pardalos on page 59, page 404, and page 487
- Optimization Theory: Recent Developments from Mátraháza (Applied Optimization) by F. Giannessi on page 31, and page 177
- Introduction to Global Optimization (Nonconvex Optimization and Its Applications (closed)) by R. Horst in Back Matter (1), and Back Matter (2)
- Handbook of Parallel Computing and Statistics (Statistics: A Series of Textbooks and Monographs) by Erricos John Kontoghiorghes on page 254, and page 255
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