tailieunhanh - Optimization in Medicine

Optimization has become pervasive in medicine. The application of computing to medical applications has opened many challenging issues and problems for both the medical computing field and the mathematical community. Mathematical techniques (continuous and discrete) are playing a key role with increasing importance in understanding several fundamental problems in medicine. Naturally, optimization is a fundamentally important tool due to the limitation of the resources involved and the need for better decision making | Springer Optimization ANU Its Applications optimization IN MEDICINE EDITED BY CARLOS . ALVES PANOS M. PARDALOS LUIS NUNES VICENTE Optimization in Medicine Springer Series in Optimization and Its Applications VOLUME 12 Managing Editor Panos M. Pardalos University of Florida Editor Combinatorial Optimization Ding-Zhu Du University of Texas at Dallas Advisory Board J. Birge University of Chicago . Floudas Princeton University F. Giannessi University of Pisa . Sherali Virginia Polytechnic and State University T. Terlaky McMaster University Y. Ye Stanford University Aims and Scope Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed the diffusion into other disciplines has proceeded at a rapid pace and our knowledge of all aspects of the field has grown even more profound. At the same time one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics engineering medicine economics and other sciences. The Springer Series in Optimization and Its Applications publishes undergraduate and graduate textbooks monographs and state-of-the-art expository works that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization convex and nonconvex network flow problems stochastic optimization optimal control discrete optimization multi-objective programming description of software packages approximation techniques and heuristic .

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