| 书目名称 | Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming | | 副标题 | Theory, Algorithms, | | 编辑 | Mohit Tawarmalani,Nikolaos V. Sahinidis | | 视频video | | | 丛书名称 | Nonconvex Optimization and Its Applications | | 图书封面 |  | | 描述 | Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models. Both of these extensions of the linear programming model are NP-hard, thus representing very challenging problems. On the brighter side, recent advances in algorithmic and computing technology make it possible to re visit these problems with the hope of solving practically relevant problems in reasonable amounts of computational time. Initial attempts at solving nonlinear programs concentrated on the de velopment of local optimization methods guarant | | 出版日期 | Book 2002 | | 关键词 | Partition; algorithm; algorithms; global optimization; linear optimization; model; nonlinear optimization; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-3532-1 | | isbn_softcover | 978-1-4419-5235-6 | | isbn_ebook | 978-1-4757-3532-1Series ISSN 1571-568X | | issn_series | 1571-568X | | copyright | Springer Science+Business Media Dordrecht 2002 |
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发表于 2025-3-21 16:32:14
