Opening book details…
Can I read Complexity in Numerical Optimization on EtoBox?
Complexity in Numerical Optimization by Pardalos P.M. (ed.) is a nonfiction available to read on EtoBox.
What is Complexity in Numerical Optimization about?
Modern day high-performance computers are making available solutions to rheological flow problems of ever-increasing complexity. Computational rheology is a fast-moving subject - problems which used to be intractable, such as 3D transient flows of polymeric liquids, non-isothermal non-Newtonian flows or flows of highly elastic liquids through complex geometries, are now being tackled owing to the availability of parallel computers, adaptive methods and advances in constitutive modelling. This work traces the development of numerical methods for non-Newtonian flows from the late 1960's to 2001. It begins with broad coverage of non-Newtonian fluids, including their mathematical modelling and analysis, before specific computational techniques are discussed. The application of these techniques to some important rheological flow problems of academic and industrial interest is then treated in a detailed exposition. Finally, the reader is kept abreast of topics at the cutting edge of research in computational applied mathematics, such as adaptivity and stochastic partial differential equations. All the topics in this book are dealt with from an elementary level
Who reads Complexity in Numerical Optimization?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Pardalos P.M. (ed.)
- Publisher
- World Scientific; World Scientific Publishing Company
- Published
- 1993
- Language
- EN
- ISBN
- 9789810214159
- Category
- nonfiction
- Subjects
- Mathematics, Computer Science, Stem
More by Pardalos P.M. (ed.)
Browse all works by Pardalos P.M. (ed.)
Similar books
- Computational Rheology — Robert G Owens; Timothy N Phillips (2002)
- Numerical Infinities and Infinitesimals in Optimization (Emergence, Complexity and Computation, 43) — Yaroslav D. Sergeyev , Renato De Leone (2022)
- Data Correcting Approaches in Combinatorial Optimization (SpringerBriefs in Optimization) — Goldengorin, Boris I., Pardalos, Panos M. (2012)
- Complexity and Approximation : Combinatorial Optimization Problems and Their Approximability Properties — Giorgio Ausiello, Alberto Marchetti-Spaccamela, Pierluigi Crescenzi, Giorgio Gambosi, Marco Protasi, Viggo Kann (auth.) (1999)
- Theory of Computational Complexity (Wiley Series in Discrete Mathematics and Optimization) — Du, Ding-Zhu; Ko, Ker-I; Ko, Ker-I (2014)
- Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems (Nonconvex Optimization and Its Applications, 42) — James Abello, Shankar Krishnan (auth.), Panos M. Pardalos (2000)
