Optimization algorithms in physics

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Optimization algorithms in physics / Alexander K. Hartmann, Heiko Rieger

資料種別:

図書

出版情報:

Berlin : Wiley-VCH, c2002

形態:

x, 372 p. ; 25 cm

著者名:

ISBN:

9783527403073 [3527403078]

書誌ID:

BA55600430

子書誌情報

フルテキスト

所蔵情報

他の版・巻

書誌詳細

注記:

Includes bibliographical references and index

主題:

Algorithms; Combinatorial optimization

言語:

英語

目次情報:

Introduction to Optimization / 1：

Bibliography

Complexity Theory / 2：

Algorithms / 2.1：

Time Complexity / 2.2：

NP Completeness / 2.3：

Programming Techniques / 2.4：

Graphs / 3：

Trees and Lists / 3.1：

Networks / 3.3：

Graph Representations / 3.4：

Basic Graph Algorithms / 3.5：

NP-Complete Graph Problems / 3.6：

Simple Graph Algorithms / 4：

The Connectivity-percolation Problem / 4.1：

Hoshen-Kopelman Algorithm / 4.1.1：

Other Algorithms for Connectivity Percolation / 4.1.2：

General Search Algorithms / 4.1.3：

Shortest-path Algorithms / 4.2：

The Directed Polymer in a Random Medium / 4.2.1：

Dijkstra's Algorithm / 4.2.2：

Label-correcting Algorithm / 4.2.3：

Minimum Spanning Tree / 4.3：

Introduction to Statistical Physics / 5：

Basics of Statistical Physics / 5.1：

Phase Transitions / 5.2：

Percolation and Finite-size Scaling / 5.3：

Magnetic Transition / 5.4：

Disordered Systems / 5.5：

Maximum-flow Methods / 6：

Random-field Systems and Diluted Antiferromagnets / 6.1：

Transformation to a Graph / 6.2：

Simple Maximum Flow Algorithms / 6.3：

Dinic's Method and the Wave Algorithm / 6.4：

Calculating all Ground States / 6.5：

Results for the RFIM and the DAFF / 6.6：

Minimum-cost Flows / 7：

Motivation / 7.1：

The Solution of the N-Line Problem / 7.2：

Convex Mincost-flow Problems in Physics / 7.3：

General Minimum-cost-flow Algorithms / 7.4：

Miscellaneous Results for Different Models / 7.5：

Genetic Algorithms / 8：

The Basic Scheme / 8.1：

Finding the Minimum of a Function / 8.2：

Ground States of One-dimensional Quantum Systems / 8.3：

Orbital Parameters of Interacting Galaxies / 8.4：

Approximation Methods for Spin Glasses / 9：

Spin Glasses / 9.1：

Experimental Results / 9.1.1：

Theoretical Approaches / 9.1.2：

Genetic Cluster-exact Approximation / 9.2：

Energy and Ground-state Statistics / 9.3：

Ballistic Search / 9.4：

Results / 9.5：

Matchings / 10：

Matching and Spin Glasses / 10.1：

Definition of the General Matching Problem / 10.2：

Augmenting Paths / 10.3：

Matching Algorithms / 10.4：

Maximum-cardinality Matching on Bipartite Graphs / 10.4.1：

Minimum-weight Perfect Bipartite Matching / 10.4.2：

Cardinality Matching on General Graphs / 10.4.3：

Minimum-weight Perfect Matching for General Graphs / 10.4.4：

Ground-state Calculations in 2d / 10.5：

Monte Carlo Methods / 11：

Stochastic Optimization: Simple Concepts / 11.1：

Simulated Annealing / 11.2：

Parallel Tempering / 11.3：

Prune-enriched Rosenbluth Method (PERM) / 11.4：

Protein Folding / 11.5：

Branch-and-bound Methods / 12：

Vertex Covers / 12.1：

Numerical Methods / 12.2：

Practical Issues / 12.3：

Software Engineering / 13.1：

Object-oriented Software Development / 13.2：

Programming Style / 13.3：

Programming Tools / 13.4：

Using Macros / 13.4.1：

Make Files / 13.4.2：

Scripts / 13.4.3：

Libraries / 13.5：

Numerical Recipes / 13.5.1：

LEDA / 13.5.2：

Creating your own Libraries / 13.5.3：

Random Numbers / 13.6：

Generating Random Numbers / 13.6.1：

Inversion Method / 13.6.2：

Rejection Method / 13.6.3：

The Gaussian Distribution / 13.6.4：

Tools for Testing / 13.7：

gdb / 13.7.1：

ddd / 13.7.2：

checkergcc / 13.7.3：

Evaluating Data / 13.8：

Data Plotting / 13.8.1：

Curve Fitting / 13.8.2：

Finite-size Scaling / 13.8.3：

Information Retrieval and Publishing / 13.9：

Searching for Literature / 13.9.1：

Preparing Publications / 13.9.2：

Index

Introduction to Optimization / 1：

Bibliography

Complexity Theory / 2：

Algorithms / 2.1：

Time Complexity / 2.2：

NP Completeness / 2.3：

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