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Optimization Theory And Related Topics

RRP $318.99

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This volume contains the proceedings of the workshop on Optimization Theory and Related Topics, held in memory of Dan Butnariu, from January 11-14, 2010, in Haifa, Israel. An active researcher in various fields of applied mathematics, Butnariu published over 80 papers. His extensive bibliography is included in this volume. The articles in this volume cover many different areas of Optimization Theory and its applications: maximal monotone operators, sensitivity estimates via Lyapunov functions, inverse Newton transforms, infinite-horizon Pontryagin principles, singular optimal control problems with state delays, descent methods for mixed variational inequalities, games on MV-algebras, ergodic convergence in subgradient optimization, applications to economics and technology planning, the exact penalty property in constrained optimization, nonsmooth inverse problems, Bregman distances, retraction methods in Banach spaces, and iterative methods for solving equilibrium problems. This volume will be of interest to both graduate students and research mathematicians.


Bio-synthetic Hybrid Materials And Bionanoparticles

RRP $609.99

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There is much interest in using biological structures for the fabrication of new functional materials. Recent developments in the particle character and behaviour of proteins and viral particles have had a major impact on the development of novel nanoparticle systems with new functions and possibilities. Bio-Synthetic Hybrid Materials and Bionanoparticles approaches the subject by covering the basics of disciplines involved as well as recent advances in new materials. The first section of the book focusses on the design and synthesis of different bionanoparticles and hybrid structures including the use of genetic modification as well as by organic synthesis. The second section of the book looks at the self-assembling behaviour of bionanoparticles to form new materials. The final section looks at bionanoparticle-based functional systems and materials including chapters on biomedical applications and electronic systems and devices. Edited by leading scientists in bionanoparticles, the book is a collaboration between scientists with different backgrounds and perspectives which will initiate the next generation of bio-based structures, materials and devices.


Process Optimization : A Statistical Approach

RRP $340.99

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PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "noisy" systems where the main emphasis is process optimization. The book can also be used as a reference text by Industrial, Quality and Process Engineers and Applied Statisticians working in industry, in particular, in semiconductor/electronics manufacturing and in biotech manufacturing industries.

The major features of PROCESS OPTIMIZATION: A Statistical Approach are:

  • It provides a complete exposition of mainstream experimental design techniques, including designs for first and second order models, response surface and optimal designs;
  • Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches;
  • Includes an extensive discussion of Robust Parameter Design (RPD) problems, including experimental design issues such as Split Plot designs and recent optimization approaches used for RPD;
  • Presents a detailed treatment of Bayesian Optimization approaches based on experimental data (including an introduction to Bayesian inference), including single and multiple response optimization and model robust optimization;
  • Provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization and more;
  • Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization;
  • Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods;
  • Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods;
  • Includes an introduction to Kriging methods and experimental design for computer experiments;
  • Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results.



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