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Analysis and Algorithms of Optimization Problems, Kazimierz Malanowski; Koichi Mizukami


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Автор: Kazimierz Malanowski; Koichi Mizukami
Название:  Analysis and Algorithms of Optimization Problems
ISBN: 9783540166603
Издательство: Springer
Классификация:




ISBN-10: 3540166602
Обложка/Формат: Paperback
Страницы: 241
Вес: 0.41 кг.
Дата издания: 01.06.1986
Серия: Lecture Notes in Control and Information Sciences
Язык: English
Размер: 244 x 170 x 14
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии


Experimental Methods for the Analysis of Optimization Algorithms

Автор: Thomas Bartz-Beielstein; Marco Chiarandini; Lu?s P
Название: Experimental Methods for the Analysis of Optimization Algorithms
ISBN: 364244590X ISBN-13(EAN): 9783642445903
Издательство: Springer
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Цена: 18167.00 р.
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Описание: With contributions from leaders in the field, this volume assesses the main issues in the experimental analysis of algorithms, examines their developmental cycle, and demonstrates how to configure and tune algorithms with advanced experimental techniques.

Models and Algorithms for Global Optimization

Автор: Aimo T?rn; Julius ?ilinskas
Название: Models and Algorithms for Global Optimization
ISBN: 1441942203 ISBN-13(EAN): 9781441942203
Издательство: Springer
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Цена: 25853.00 р.
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Описание: The research of Antanas Zilinskas has focused on developing models for global optimization, implementing and investigating the corresponding algorithms, and applying those algorithms to practical problems.

Genetic Algorithms And Robotics: A Heuristic Strategy For Optimization

Автор: Davidor Yuval
Название: Genetic Algorithms And Robotics: A Heuristic Strategy For Optimization
ISBN: 9810202172 ISBN-13(EAN): 9789810202170
Издательство: World Scientific Publishing
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Цена: 6494.00 р.
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Описание: Classical optimization methodologies fall short in very large and complex domains. In this book is suggested a different approach to optimization, an approach which is based on the 'blind' and heuristic mechanisms of evolution and population genetics. The genetic approach to optimization introduces a new philosophy to optimization in general, but particularly to engineering. By introducing the 'genetic' approach to robot trajectory generation, much can be learned about the adaptive mechanisms of evolution and how these mechanisms can solve real world problems. It is suggested further that optimization at large may benefit greatly from the adaptive optimization exhibited by natural systems when attempting to solve complex optimization problems, and that the determinism of classical optimization models may sometimes be an obstacle in nonlinear systems.This book is unique in that it reports in detail on an application of genetic algorithms to a real world problem, and explains the considerations taken during the development work. Futhermore, it addresses robotics in two new aspects: the optimization of the trajectory specification which has so far been done by human operators and has not received much attention for both automation and optimization, and the introduction of a heuristic strategy to a field predominated by deterministic strategies.Request Inspection Copy

Perturbation Analysis of Optimization Problems

Автор: J.Frederic Bonnans; Alexander Shapiro
Название: Perturbation Analysis of Optimization Problems
ISBN: 1461271290 ISBN-13(EAN): 9781461271291
Издательство: Springer
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Цена: 32142.00 р.
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Описание: The main subject of this book is perturbation analysis of continuous optimization problems. In the last two decades considerable progress has been made in that area, and it seems that it is time now to present a synthetic view of many important results that apply to various classes of problems. The model problem that is considered throughout the book is of the form (P) Min/(x) subjectto G(x) E K. xeX Here X and Y are Banach spaces, K is a closed convex subset of Y, and /: X -+ IR and G: X -+ Y are called the objective function and the constraint mapping, respectively. We also consider a parameteriZed version (P ) of the above u problem, where the objective function / (x, u) and the constraint mapping G(x, u) are parameterized by a vector u varying in a Banach space U. Our aim is to study continuity and differentiability properties of the optimal value v(u) and the set S(u) of optimal solutions of (P ) viewed as functions of the parameter vector u.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 27712.00 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques

Автор: Chandra Chekuri; Klaus Jansen; Jos? D.P. Rolim; Lu
Название: Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques
ISBN: 3540282394 ISBN-13(EAN): 9783540282396
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Contains 41 reviewed papers, selected by the two program committees from a total of 101 submissions. Among the issues addressed are design and analysis of approximation algorithms, hardness of approximation, small space and data streaming algorithms, sub-linear time algorithms, embeddings and metric space methods, and more.

Gems of Combinatorial Optimization and Graph Algorithms

Автор: Andreas S. Schulz; Martin Skutella; Sebastian Stil
Название: Gems of Combinatorial Optimization and Graph Algorithms
ISBN: 3319249703 ISBN-13(EAN): 9783319249704
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? This volume is aimed at readers with some familiarity of combinatorial optimization, and appeals to researchers, graduate students, and advanced undergraduate students alike.

Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques

Автор: Michel Goemans; Klaus Jansen; Jose D.P. Rolim; Luc
Название: Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques
ISBN: 3540424709 ISBN-13(EAN): 9783540424703
Издательство: Springer
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Цена: 9781.00 р.
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Описание: These are the joint refereed proceedings of the 4th International Workshop on Approximation Algorithms for Optimization Problems, APPROX 2001 and of the 5th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2001.

Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures

Автор: Ron Alterovitz; Ken Goldberg
Название: Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures
ISBN: 3642088740 ISBN-13(EAN): 9783642088742
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Written by Ron Alterovitz and Ken Goldberg, this monograph combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures.

Geometric Algorithms and Combinatorial Optimization

Автор: Martin Gr?tschel; Laszlo Lovasz; Alexander Schrijv
Название: Geometric Algorithms and Combinatorial Optimization
ISBN: 3642782426 ISBN-13(EAN): 9783642782428
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Moreover, despite the success of the interior point methods for the solution of explicitly given linear programs there is still no method known that solves implicitly given linear programs, such as those described in this book, and that is both practically and theoretically efficient.

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132235398 ISBN-13(EAN): 9788132235392
Издательство: Springer
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Цена: 14365.00 р.
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Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Автор: Muhammet ?nal; Ay?a Ak; Vedat Topuz; Hasan Erdal
Название: Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
ISBN: 3642434770 ISBN-13(EAN): 9783642434778
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book covers the theory behind artificial neural networks, genetic algorithms and the ant colony optimization algorithm, and presents a novel real time control algorithm using genetic and ant colony optimization algorithms for optimizing PID controllers.


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