Probabilistic Analysis of Some Combinatorial Optimization Problems on Networks

Probabilistic Analysis of Some Combinatorial Optimization Problems on Networks PDF Author: Anjani Jain
Publisher:
ISBN:
Category : Combinatorial optimization
Languages : en
Pages : 148

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Complexity and Approximation

Complexity and Approximation PDF Author: Giorgio Ausiello
Publisher: Springer Science & Business Media
ISBN: 3642584128
Category : Computers
Languages : en
Pages : 536

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Book Description
This book documents the state of the art in combinatorial optimization, presenting approximate solutions of virtually all relevant classes of NP-hard optimization problems. The wealth of problems, algorithms, results, and techniques make it an indispensible source of reference for professionals. The text smoothly integrates numerous illustrations, examples, and exercises.

Probability Theory and Combinatorial Optimization

Probability Theory and Combinatorial Optimization PDF Author: J. Michael Steele
Publisher: SIAM
ISBN: 0898713803
Category : Mathematics
Languages : en
Pages : 164

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Book Description
An introduction to the state of the art of the probability theory most applicable to combinatorial optimization. The questions that receive the most attention are those that deal with discrete optimization problems for points in Euclidean space, such as the minimum spanning tree, the traveling-salesman tour, and minimal-length matchings.

Combinatorial Optimization

Combinatorial Optimization PDF Author: M. O'hEigeartaigh
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 220

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Surveys in Combinatorial Optimization

Surveys in Combinatorial Optimization PDF Author: S. Martello
Publisher: Elsevier
ISBN: 0080872433
Category : Mathematics
Languages : en
Pages : 395

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Book Description
A collection of papers surveying recent progress in the field of Combinatorial Optimization. Topics examined include theoretical and computational aspects (Boolean Programming, Probabilistic Analysis of Algorithms, Parallel Computer Models and Combinatorial Algorithms), well-known combinatorial problems (such as the Linear Assignment Problem, the Quadratic Assignment Problem, the Knapsack Problem and Steiner Problems in Graphs) and more applied problems (such as Network Synthesis and Dynamic Network Optimization, Single Facility Location Problems on Networks, the Vehicle Routing Problem and Scheduling Problems).

Probabilistic Combinatorial Optimization on Graphs

Probabilistic Combinatorial Optimization on Graphs PDF Author: Cécile Murat
Publisher: John Wiley & Sons
ISBN: 1118614135
Category : Mathematics
Languages : en
Pages : 202

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Book Description
This title provides a comprehensive survey over the subject of probabilistic combinatorial optimization, discussing probabilistic versions of some of the most paradigmatic combinatorial problems on graphs, such as the maximum independent set, the minimum vertex covering, the longest path and the minimum coloring. Those who possess a sound knowledge of the subject mater will find the title of great interest, but those who have only some mathematical familiarity and knowledge about complexity and approximation theory will also find it an accessible and informative read.

Probabilistic Analysis of Algorithms

Probabilistic Analysis of Algorithms PDF Author: Micha Hofri
Publisher: Springer Science & Business Media
ISBN: 1461248000
Category : Computers
Languages : en
Pages : 254

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Book Description
Probabilistic Analysis of Algorithms begins with a presentation of the "tools of the trade" currently used in probabilistic analyses, and continues with an applications section in which these tools are used in the analysis ofr selected algorithms. The tools section of the book provides the reader with an arsenal of analytic and numeric computing methods which are then applied to several groups of algorithms to analyze their running time or storage requirements characteristics. Topics covered in the applications section include sorting, communications network protocols and bin packing. While the discussion of the various algorithms is sufficient to motivate their structure, the emphasis throughout is on the probabilistic estimation of their operation under distributional assumptions on their input. Probabilistic Analysis of Algorithms assumes a working knowledge of engineering mathematics, drawing on real and complex analysis, combinatorics and probability theory. While the book is intended primarily as a text for the upper undergraduate and graduate student levels, it contains a wealth of material and should also prove an important reference for researchers. As such it is addressed to computer scientists, mathematicians, operations researchers, and electrical and industrial engineers who are interested in evaluating the probable operation of algorithms, rather than their worst-case behavior.

Probability and Computing

Probability and Computing PDF Author: Michael Mitzenmacher
Publisher: Cambridge University Press
ISBN: 9780521835404
Category : Computers
Languages : en
Pages : 372

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Book Description
Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.

Paradigms of Combinatorial Optimization

Paradigms of Combinatorial Optimization PDF Author: Vangelis Th. Paschos
Publisher: John Wiley & Sons
ISBN: 1118600185
Category : Mathematics
Languages : en
Pages : 483

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Book Description
Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. “Paradigms of Combinatorial Optimization” is divided in two parts: • Paradigmatic Problems, that handles several famous combinatorial optimization problems as max cut, min coloring, optimal satisfiability tsp, etc., the study of which has largely contributed to both the development, the legitimization and the establishment of the Combinatorial Optimization as one of the most active actual scientific domains; • Classical and New Approaches, that presents the several methodological approaches that fertilize and are fertilized by Combinatorial optimization such as: Polynomial Approximation, Online Computation, Robustness, etc., and, more recently, Algorithmic Game Theory.

Probabilistic Analysis of Packing and Partitioning Algorithms

Probabilistic Analysis of Packing and Partitioning Algorithms PDF Author: Edward Grady Coffman
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 216

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Book Description
This volume examines two important classes that are characteristic of combinatorial optimization problems: sequencing and scheduling (in which a set of objects has to be ordered subject to a number of conditions), and packing and partitioning (in which a set of objects has to be split into subsets in order to meet a certain objective). These classes of problems encompass a wide range of practical applications, from production planning and flexible manufacturing to computer scheduling and