Computational Optimization Techniques and Applications
This unique book describes how the General Algebraic Modeling System (GAMS) can be used to solve various power system operation and planning optimization problems. This book is the first of its kind to provide readers with a comprehensive reference that includes the solution codes for basic/advanced power system optimization problems in GAMS, a computationally efficient tool for analyzing optimization problems in power and energy systems. The book covers theoretical background as well as the app...
Hamilton-Jacobi-Bellman Equations (Radon Series on Computational and Applied Mathematics)
Optimal feedback control arises in different areas such as aerospace engineering, chemical processing, resource economics, etc. In this context, the application of dynamic programming techniques leads to the solution of fully nonlinear Hamilton-Jacobi-Bellman equations. This book presents the state of the art in the numerical approximation of Hamilton-Jacobi-Bellman equations, including post-processing of Galerkin methods, high-order methods, boundary treatment in semi-Lagrangian schemes, reduce...
This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world appli...
Modern Optimization Methods for Science, Engineering and Technology (IOP ebooks)
This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition. Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms than...
Statistical Modeling with Matlab. Functions for Calibration Models
by Olsen F
Practical Optimization (Classics in Applied Mathematics)
by Philip E. Gill, Walter Murray, and Margaret H. Wright
In the intervening years since this book was published in 1981, the field of optimization has been exceptionally lively. This fertility has involved not only progress in theory, but also faster numerical algorithms and extensions into unexpected or previously unknown areas such as semidefinite programming. Despite these changes, many of the important principles and much of the intuition can be found in this Classics version of Practical Optimization. This book provides model algorithms and pseu...
60 Worksheets - Identifying Smallest Number of 7 Digits (60 Days Math Smallest Numbers, #6)
by Kapoo Stem
Signal Processing
by Fredrik Gustafsson, Lennart Ljung, and Mille Millnert
A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author-a noted expert in the field-covers a wide range of topics including mathematical...
This is the first book that focuses on practical algorithms for polynomial inequality proving and discovering. It is a summary of the work by the authors and their collaborators on automated inequality proving and discovering in recent years. Besides brief introduction to some classical results and related work in corresponding chapters, the book mainly focuses on the algorithms initiated by the authors and their collaborators, such as real root counting, real root classification, improved CAD p...
Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing. Providing researchers, practitioners, and academicians with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization, this book compile the latest findings, analysis, improvements, and applications of technologi...
Ant Colony Optimization (Ant Colony Optimization)
by Marco Dorigo and Thomas Stutzle
The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant beh...
Optimal Investment and Marketing Strategies (Systems Research, #2)
by Ilona Murynets
Over the past decade, innovative technologies have resulted in an extensive growth of new services. Each new service requires a number of management and marketing decisions to be made well in advance of its launch and throughout its entire life cycle. This book develops mathematical models to facilitate decision-making dealing with technologically innovative services. Specifically, it develops (i) models for optimal pricing strategies of subscription services on monopolistic and duopolistic mark...
The topic of this thesis originated in the task to optimize a belt-shaped textile structure with respect to buckling. The approach is divided into two main steps: asymptotic analysis and optimization. First, we show the simultaneous homogenization and dimension reduction for the textile elasticity problem using the unfolding method. In particular, the effective model is derived for different energy regimes, depending on periodicity, applied force and fiber-to-fiber contact. The different energy...
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numeri...
Numerical Linear Algebra And Optimization
by Philip E. Gill and Walter Murray
By discussing topics such as shape representations, relaxation theory and optimal transport, trends and synergies of mathematical tools required for optimization of geometry and topology of shapes are explored. Furthermore, applications in science and engineering, including economics, social sciences, biology, physics and image processing are covered. Contents Part I Geometric issues in PDE problems related to the infinity Laplace operator Solution of free boundary problems in the pre...
The revised and updated new edition of the popular optimization book for engineers The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author--a noted expert on the topic--presents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles...
Collected Works Of Marida Bertocchi (World Scientific Handbook in Financial Economics, #8)
The volume provides information on the career and life of Marida Bertocchi, and is representative of her broad research interests on the development of numerical algorithms and their applications in energy, finance and logistics. It includes some of her early publications, her significant papers on the development and application of stochastic optimization to financial and logistics problems, and her later work on robust optimization for risk management in renewable energy systems, finance and l...
Computational Optimization and Applications
by Kajla Basu and Samarjit Kar
Most of the real world problems arising in engineering, economics, management, finance, medicine and other domains can be formulated as optimization tasks. These problems are frequently characterized by non-convex, non-differentiable, discontinuous, noisy or dynamic objective functions and constraints which ask for adequate computational methods. The aim of this book is to stimulate the communication between researchers from different fields of optimization and practitioners who need reliable an...