Phase Transitions in Combinatorial Optimization Problems

This book PDF is perfect for those who love Science genre, written by Alexander K. Hartmann and published by John Wiley & Sons which was released on 12 May 2006 with total hardcover pages 360. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Phase Transitions in Combinatorial Optimization Problems books below.

Phase Transitions in Combinatorial Optimization Problems
Phase Transitions in Combinatorial Optimization Problems
Author : Alexander K. Hartmann
File Size : 44,6 Mb
Publisher : John Wiley & Sons
Language : English
Release Date : 12 May 2006
ISBN : 9783527606863
Pages : 360 pages
Get Book

Phase Transitions in Combinatorial Optimization Problems by Alexander K. Hartmann Book PDF Summary

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

Phase Transitions in Combinatorial Optimization Problems

Phase Transitions in Combinatorial Optimization Problems by Alexander K. Hartmann,Martin Weigt

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with

Get Book
Optimization Algorithms in Physics

Optimization Algorithms in Physics by Alexander K. Hartmann,Heiko Rieger

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

Get Book
Extremal Optimization

Extremal Optimization by Yong-Zai Lu,Yu-Wang Chen,Min-Rong Chen,Peng Chen,Guo-Qiang Zeng

Extremal Optimization: Fundamentals, Algorithms, and Applications introduces state-of-the-art extremal optimization (EO) and modified EO (MEO) solutions from fundamentals, methodologies, and algorithms to applications based on numerous classic publications and the authors’ recent original research results. It promotes the movement of EO from academic study to practical applications. The book covers

Get Book
Phase Transitions in Machine Learning

Phase Transitions in Machine Learning by Lorenza Saitta,Attilio Giordana,Antoine Cornuéjols

Phase transitions typically occur in combinatorial computational problems and have important consequences, especially with the current spread of statistical relational learning as well as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin by describing in detail this phenomenon, and the extensive experimental investigation that supports its

Get Book
Computational Complexity and Statistical Physics

Computational Complexity and Statistical Physics by Allon Percus,Gabriel Istrate,Cristopher Moore

Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze

Get Book
An Introduction to Metaheuristics for Optimization

An Introduction to Metaheuristics for Optimization by Bastien Chopard,Marco Tomassini

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for

Get Book
Evolutionary Computation in Combinatorial Optimization

Evolutionary Computation in Combinatorial Optimization by Bin Hu,Manuel López-Ibáñez

This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both

Get Book
New Optimization Algorithms in Physics

New Optimization Algorithms in Physics by Alexander K. Hartmann,Heiko Rieger

Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have not been presented comprehensively until now. This presentation of recently developed algorithms applied in physics, including demonstrations of how

Get Book