Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Optimization Methods in Finance
Full treatment, from model formulation to computational implementation, of optimization techniques that solve central problems in finance.
Integer Programming
This book is an elegant and rigorous presentation of integer programming, exposing the subject’s mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory. Each chapter is accompanied by an expertly informed guide to the literature and special topics, rounding out the reader’s understanding and serving as a gateway to deeper study. Key topics include: formulations polyhedral theory cutting planes decomposition enumeration semidefinite relaxations Written by renowned experts in integer programming and combinatorial optimization, Integer Programming is destined to become an essential text in the field.
Integer Programming
None
Optimization Methods in Finance
Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.
Combinatorial Optimization
New and elegant proofs of classical results and makes difficult results accessible.
Combinatorial Optimization
This monograph presents new and elegant proofs of classical results and makes difficult results accessible. The integer programming models known as set packing and set covering have a wide range of applications. Sometimes, owing to the special structure of the constraint matrix, the natural linear programming relaxation yields an optimal solution that is integral, thus solving the problem. Sometimes, both the linear programming relaxation and its dual have integral optimal solutions. Under which conditions do such integrality conditions hold? This question is of both theoretical and practical interest. Min-max theorems, polyhedral combinatorics, and graph theory all come together in this rich area of discrete mathematics. This monograph presents several of these beautiful results as it introduces mathematicians to this active area of research.
A Gentle Introduction to Optimization
Assuming only basic linear algebra, this textbook is the perfect starting point for undergraduate students from across the mathematical sciences.
Integer Programming and Combinatorial Optimization
This book constitutes the refereed proceedings of the 7th International Conference on Integer Programming and Combinatorial Optimization, IPCO'99, held in Graz, Austria, in June 1999. The 33 revised full papers presented were carefully reviewed and selected from a total of 99 submissions. Among the topics addressed are theoretical, computational, and application-oriented aspects of approximation algorithms, branch and bound algorithms, computational biology, computational complexity, computational geometry, cutting plane algorithms, diaphantine equations, geometry of numbers, graph and network algorithms, online algorithms, polyhedral combinatorics, scheduling, and semidefinite programs.
Introduction to Optimization and Semidifferential Calculus
This primarily undergraduate textbook focuses on finite-dimensional optimization. Readers will find: an original and well integrated treatment of semidifferential calculus and optimization; emphasis on the Hadamard subdifferential, introduced at the beginning of the 20th century and somewhat overlooked for many years, with references to original papers by Hadamard (1923) and Fréchet (1925); fundamentals of convex analysis (convexification, Fenchel duality, linear and quadratic programming, two-person zero-sum games, Lagrange primal and dual problems, semiconvex and semiconcave functions); complete definitions, theorems, and detailed proofs, even though it is not necessary to work through all of them; commentaries that put the subject into historical perspective; numerous examples and exercises throughout each chapter, and answers to the exercises provided in an appendix.
