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Iterative Methods in Combinatorial Optimization

Iterative Methods in Combinatorial Optimization
Author: Lap Chi Lau
Publisher: Cambridge University Press
Total Pages: 255
Release: 2011-04-18
Genre: Computers
ISBN: 1139499394

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With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.


Handbook of Combinatorial Optimization

Handbook of Combinatorial Optimization
Author: Ding-Zhu Du
Publisher: Springer Science & Business Media
Total Pages: 660
Release: 1999-10-31
Genre: Business & Economics
ISBN: 9780792359241

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This volume can be considered as a supplementary volume to the major three-volume Handbook of Combinatorial Optimization published by Kluwer. It can also be regarded as a stand-alone volume which presents chapters dealing with various aspects of the subject including optimization problems and algorithmic approaches for discrete problems. Audience: All those who use combinatorial optimization methods to model and solve problems.


Iterative Computer Algorithms with Applications in Engineering

Iterative Computer Algorithms with Applications in Engineering
Author: Sadiq M. Sait
Publisher: Wiley-IEEE Computer Society Press
Total Pages: 418
Release: 1999
Genre: Computers
ISBN:

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Iterative Computer Algorithms with Applications in Engineering describes in-depth the five main iterative algorithms for solving hard combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search, Simulated Evolution, and Stochastic Evolution. The authors present various iterative techniques and illustrate how they can be applied to solve several NP-hard problems. For each algorithm, the authors present the procedures of the algorithm, parameter selection criteria, convergence property analysis, and parallelization. There are also several real-world examples that illustrate various aspects of the algorithms. The book includes an introduction to fuzzy logic and its application in the formulation of multi-objective optimization problems, a discussion on hybrid techniques that combine features of heuristics, a survey of recent research work, and examples that illustrate required mathematical concepts. The unique features of this book are: An integrated and up-to-date description of iterative non-deterministic algorithms; Detailed descriptions of Simulated Evolution and Stochastic Evolution; A level of treatment suitable for first year graduate student and practicing engineers; Parallelization aspects and particular parallel implementations; A brief survey of recent research work; Graded exercises and an annotated bibliography in each chapter


Iterative Methods for Optimization

Iterative Methods for Optimization
Author: C. T. Kelley
Publisher: SIAM
Total Pages: 195
Release: 1999-01-01
Genre: Mathematics
ISBN: 9781611970920

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This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.


The Linear Ordering Problem

The Linear Ordering Problem
Author: Rafael Martí
Publisher: Springer Science & Business Media
Total Pages: 181
Release: 2011-01-03
Genre: Computers
ISBN: 3642167292

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Faced with the challenge of solving the hard optimization problems that abound in the real world, existing methods often encounter great difficulties. Important applications in business, engineering or economics cannot be tackled by the techniques that have formed the predominant focus of academic research throughout the past three decades. Exact and heuristic approaches are dramatically changing our ability to solve problems of practical significance and are extending the frontier of problems that can be handled effectively. This monograph details state-of-the-art optimization methods, both exact and heuristic, for the LOP. The authors employ the LOP to illustrate contemporary optimization technologies as well as how to design successful implementations of exact and heuristic procedures. Therefore, they do not limit the scope of this book to the LOP, but on the contrary, provide the reader with the background and practical strategies in optimization to tackle different combinatorial problems.


The Cross-Entropy Method

The Cross-Entropy Method
Author: Reuven Y. Rubinstein
Publisher: Springer Science & Business Media
Total Pages: 316
Release: 2013-03-09
Genre: Computers
ISBN: 1475743211

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Rubinstein is the pioneer of the well-known score function and cross-entropy methods. Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.


Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
Author: Josep Diaz
Publisher: Springer Science & Business Media
Total Pages: 532
Release: 2006-08-11
Genre: Computers
ISBN: 3540380442

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This is the joint refereed proceedings of the 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 and the 10th International Workshop on Randomization and Computation, RANDOM 2006. The book presents 44 carefully reviewed and revised full papers. Among the topics covered are design and analysis of approximation algorithms, hardness of approximation problems, small spaces and data streaming algorithms, embeddings and metric space methods, and more.


Combinatorial Optimization

Combinatorial Optimization
Author: Bernhard Korte
Publisher: Springer Science & Business Media
Total Pages: 596
Release: 2006-01-27
Genre: Mathematics
ISBN: 3540292977

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This well-written textbook on combinatorial optimization puts special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. The book contains complete (but concise) proofs, as well as many deep results, some of which have not appeared in any previous books.


Nonlinear Combinatorial Optimization

Nonlinear Combinatorial Optimization
Author: Ding-Zhu Du
Publisher: Springer
Total Pages: 315
Release: 2019-05-31
Genre: Mathematics
ISBN: 3030161943

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Graduate students and researchers in applied mathematics, optimization, engineering, computer science, and management science will find this book a useful reference which provides an introduction to applications and fundamental theories in nonlinear combinatorial optimization. Nonlinear combinatorial optimization is a new research area within combinatorial optimization and includes numerous applications to technological developments, such as wireless communication, cloud computing, data science, and social networks. Theoretical developments including discrete Newton methods, primal-dual methods with convex relaxation, submodular optimization, discrete DC program, along with several applications are discussed and explored in this book through articles by leading experts.