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Optimization algorithms in physics
Saved in:
Other Authors:  Rieger, Heiko [Other] 

Edition:  1st ed 
Type of Resource:  EBook 
Language:  English 
published: 
Berlin
WileyVCH
©2002

Subjects:  
Source:  Verbunddaten SWB 
ISBN: 
1280558547
3527403078 3527600876 9783527403073 9783527600878 9781280558542 
Summary: 
Ch. 1. Introduction to Optimization, p. 17  ch. 2. Complexity Theory, p. 935  ch. 3. Graphs, p. 3752  ch. 4. Simple Graph Algorithms, p. 5372  ch. 5. Introduction to Statistical Physics, p. 7390  ch. 6. MaximumFlow Methods, p. 91127  ch. 7. MinimumCost Flows, p. 129157  ch. 8. Genetic Algorithms, p. 159184  ch. 9. Approximation Methods for Spin Glasses, p. 185226  ch. 10. Matchings, p. 227254  ch. 11. Monte Carlo Methods, p. 255272  ch. 12. BranchandBound Methods, p. 273292  ch. 13. Practical Issues, p. 293357. The past few years have witnessed a substantial growth in the number of applications for optimization algorithms in solving problems in the field of physics. Examples include determining the structure of molecules, estimating the parameters of interacting galaxies, the ground states of electronic quantum systems, the behavior of disordered magnetic materials, and phase transitions in combinatorial optimization problems. This book serves as an introduction to the field, while also presenting a complete overview of modern algorithms. The authors begin with the relevant foundations from computer science, graph theory and statistical physics, before moving on to thoroughly explain algorithms  backed by illustrative examples. They include pertinent mathematical transformations, which in turn are used to make the physical problems tractable with methods from combinatorial optimization. Throughout, a number of interesting results are shown for all physical examples. The final chapter provides numerous practical hints on software development, testing programs, and evaluating the results of computer experiments 

Item Description:  Includes bibliographical references and index 
Physical Description:  1 OnlineRessource (x, 372 pages); illustrations 
ISBN: 
1280558547
3527403078 3527600876 9783527403073 9783527600878 9781280558542 
DOI:  10.1002/3527600876 