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The Resource Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst
Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst
Resource Information
The item Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
- Summary
- Simulated annealing is a solution method in the field of combinatorial optimization based on an analogy with the physical process of annealing. The method is generally applicable, and can obtain solutions arbitrarily close to an optimum. However, finding high quality solutions can require large computational effort. The computational effort required can be greatly reduced by using the computational model of the Boltzmann machine. This is a neural network model which belongs to the class of connectionist models. It is characterized by massive parallelism and distributed representations. These features lead to a conceptually simple yet powerful model, which can be seen as an architectural blueprint for future parallel computers which can cope with higher order optimization problems such as learning. This book brings together in one volume the theory of simulated annealing and the model of the Boltzmann machine. It combines a mathematical treatment with a clear view of the applications which are already possible and the exciting developments which are beginning. It will be of great interest to graduate students and researchers in combinatorial optimization, numerical optimization, parallel processing, neural networks, computer science, artificial intelligence and automaton theory
- Language
- eng
- Extent
- xii, 272 pages
- Note
- Includes indexes
- Contents
-
- pt. I. Simulated annealing. 1. Combinatorial optimization
- 2. Simulated annealing
- 3. Asymptotic convergence
- 4. Finite-time approximation
- 5. Simulated annealing in practice
- 6. Parallel simulated annealing algorithms
- pt. II. Boltzmann machines. 7. Neural computing
- 8. Boltzmann machines
- 9. Combinatorial optimization and Boltzmann machines
- 10. Classification and Boltzmann machines
- 11. Learning and Boltzmann machines
- Appendix: The EUR100 problem instance
- Isbn
- 9780471921462
- Label
- Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing
- Title
- Simulated annealing and Boltzmann machines
- Title remainder
- a stochastic approach to combinatorial optimization and neural computing
- Statement of responsibility
- Emile Aarts, Jan Korst
- Subject
-
- Automates mathématiques, Théorie des
- Automates mathématiques, Théorie des
- Combinatieleer
- Computers
- Machine theory
- Machine theory
- Mathematics | Combinatorial optimisation
- Neural computers
- Neural computers
- Neurale netwerken
- Optimaliseren
- Optimisation combinatoire
- Optimisation combinatoire
- Ordinateurs neuronaux
- Ordinateurs neuronaux
- Parallelle verwerking
- Recuit simulé
- Recuit simulé (mathématiques)
- Réseau neuronal
- Simulated annealing (Mathematics)
- Simulated annealing (Mathematics)
- Algorithme recuit simulé
- Language
- eng
- Summary
- Simulated annealing is a solution method in the field of combinatorial optimization based on an analogy with the physical process of annealing. The method is generally applicable, and can obtain solutions arbitrarily close to an optimum. However, finding high quality solutions can require large computational effort. The computational effort required can be greatly reduced by using the computational model of the Boltzmann machine. This is a neural network model which belongs to the class of connectionist models. It is characterized by massive parallelism and distributed representations. These features lead to a conceptually simple yet powerful model, which can be seen as an architectural blueprint for future parallel computers which can cope with higher order optimization problems such as learning. This book brings together in one volume the theory of simulated annealing and the model of the Boltzmann machine. It combines a mathematical treatment with a clear view of the applications which are already possible and the exciting developments which are beginning. It will be of great interest to graduate students and researchers in combinatorial optimization, numerical optimization, parallel processing, neural networks, computer science, artificial intelligence and automaton theory
- Cataloging source
- DLC
- http://library.link/vocab/creatorName
- Aarts, E. H. L.
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QA402.5
- LC item number
- .A22 1989
- Literary form
- non fiction
- Nature of contents
- bibliography
- http://library.link/vocab/relatedWorkOrContributorName
- Korst, Jan
- Series statement
- Wiley-Interscience series in discrete mathematics and optimization.
- http://library.link/vocab/subjectName
-
- Simulated annealing (Mathematics)
- Machine theory
- Neural computers
- Algorithme recuit simulé
- Réseau neuronal
- Recuit simulé
- Automates mathématiques, Théorie des
- Ordinateurs neuronaux
- Optimisation combinatoire
- Machine theory
- Neural computers
- Simulated annealing (Mathematics)
- Combinatieleer
- Neurale netwerken
- Optimaliseren
- Parallelle verwerking
- Computers
- Automates mathématiques, Théorie des
- Ordinateurs neuronaux
- Recuit simulé (mathématiques)
- Optimisation combinatoire
- Label
- Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst
- Note
- Includes indexes
- Bibliography note
- Bibliography: p. 243-258
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- pt. I. Simulated annealing. 1. Combinatorial optimization -- 2. Simulated annealing -- 3. Asymptotic convergence -- 4. Finite-time approximation -- 5. Simulated annealing in practice -- 6. Parallel simulated annealing algorithms -- pt. II. Boltzmann machines. 7. Neural computing -- 8. Boltzmann machines -- 9. Combinatorial optimization and Boltzmann machines -- 10. Classification and Boltzmann machines -- 11. Learning and Boltzmann machines -- Appendix: The EUR100 problem instance
- Dimensions
- 24 cm.
- Extent
- xii, 272 pages
- Isbn
- 9780471921462
- Lccn
- 88020871
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- Other physical details
- illustrations
- System control number
-
- (OCoLC)18381004
- (OCoLC)ocm18381004
- Label
- Simulated annealing and Boltzmann machines : a stochastic approach to combinatorial optimization and neural computing, Emile Aarts, Jan Korst
- Note
- Includes indexes
- Bibliography note
- Bibliography: p. 243-258
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- pt. I. Simulated annealing. 1. Combinatorial optimization -- 2. Simulated annealing -- 3. Asymptotic convergence -- 4. Finite-time approximation -- 5. Simulated annealing in practice -- 6. Parallel simulated annealing algorithms -- pt. II. Boltzmann machines. 7. Neural computing -- 8. Boltzmann machines -- 9. Combinatorial optimization and Boltzmann machines -- 10. Classification and Boltzmann machines -- 11. Learning and Boltzmann machines -- Appendix: The EUR100 problem instance
- Dimensions
- 24 cm.
- Extent
- xii, 272 pages
- Isbn
- 9780471921462
- Lccn
- 88020871
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- Other physical details
- illustrations
- System control number
-
- (OCoLC)18381004
- (OCoLC)ocm18381004
Subject
- Automates mathématiques, Théorie des
- Automates mathématiques, Théorie des
- Combinatieleer
- Computers
- Machine theory
- Machine theory
- Mathematics | Combinatorial optimisation
- Neural computers
- Neural computers
- Neurale netwerken
- Optimaliseren
- Optimisation combinatoire
- Optimisation combinatoire
- Ordinateurs neuronaux
- Ordinateurs neuronaux
- Parallelle verwerking
- Recuit simulé
- Recuit simulé (mathématiques)
- Réseau neuronal
- Simulated annealing (Mathematics)
- Simulated annealing (Mathematics)
- Algorithme recuit simulé
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