Издательство InTech, 2010, -300 pp.
This book presents recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine.
The book contains 15 research papers. Chapters 1 to 3 address inverse problems or parameter identification problems. These problems arise from the necessity of obtaining parameters of theoretical models in such a way that the models can be used to simulate the behaviour of the system for different operating conditions. Chapter 1 presents the parameter identification problem for power semiconductor models and chapter 2 for heat and mass transfer problems. Chapter 3 discusses the use of SA in radiotherapy treatment planning and presents recent work to apply SA in interstitial light therapies. The usefulness of solving an inverse problem is clear in this application: instead of manually specifying the treatment parameters and repeatedly evaluating the resulting radiation dose distribution, a desired dose distribution is prescribed by the physician and the task of finding the appropriate treatment parameters is automated with an optimisation algorithm.
Chapters 4 and 5 present two applications in Telecommunications field. Chapter 4 discusses the optimal design and formation of micromobility domains for extending location privacy protection capabilities of micromobility protocols. In chapter 5 SA is used for large-scale IP traffic matrix estimation, which is used by network operators to conduct network management, network planning and traffic detecting.
Chapter 6 and 7 present two SA applications in Geology and Molecular Biology fields, particularly the optimisation problem of land sampling schemes for land characterisation and primer design for PCR processes, respectively.
Some Electrical Engineering applications are analysed in chapters 8 to
11. Chapter 8 deals with network reconfiguration for reliability worth enhancement in electrical distribution systems. The optimal design of an interior permanent magnet motor for power steering applications is discussed in chapter
9. In chapter 10 SA is used for optimal control systems design and in chapter 11 for feature selection and dimensionality reduction for image classification tasks. Chapters 12 to 15 provide some depth to SA theory and comparative studies with other optimisation algorithms. There are several parameters in the process of annealing whose values affect the overall performance. Chapter 12 focuses on the initial temperature and proposes a new approach to set this control parameter. Chapter 13 presents improved approaches on the multilevel hierarchical floorplan/placement for large-scale circuits. An improved format of !-neighborhood and !-exchange algorithm in SA is used. In chapter 14 SA performance is compared with Steepest Ascent and Ant Colony Optimization as well as an hybridisation version. Control of adaptive optics system that compensates variations in the speed of light propagation is presented in last chapter. Here SA is also compared with Genetic Algorithm, Stochastic Parallel Gradient Descent and Algorithm of Patte extraction.
Parameter identification of power semiconductor device models using metaheuristics.
Application of simulated annealing and hybrid methods in the solution of inverse heat and mass transfer problems.
Towards conformal interstitial light therapies: Modelling parameters, dose definitions and computational implementation.
A Location Privacy Aware Network Planning Algorithm for Micromobility Protocols.
Simulated Annealing-Based Large-scale IP Traffic Matrix Estimation.
Field sampling scheme optimization using simulated annealing.
Customized Simulated Annealing Algorithm Suitable for Primer Design in Polymerase Chain Reaction Processes.
Network Reconfiguration for Reliability Worth Enhancement in Distribution System by Simulated Annealing.
Optimal Design of an IPM Motor for Electric Power Steering Application Using Simulated Annealing Method.
Using the simulated annealing algorithm to solve the optimal control problem.
A simulated annealing band selection approach for high-dimensional remote sensing images.
Importance of the initial conditions and the time schedule in the Simulated Annealing.
Multilevel Large-Scale Modules Floorplanning/Placement with Improved Neighborhood Exchange in Simulated Annealing.
Simulated Annealing and its Hybridisation on Noisy and Constrained Response Surface Optimisations.
Simulated Annealing for Control of Adaptive Optics System.
This book presents recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine.
The book contains 15 research papers. Chapters 1 to 3 address inverse problems or parameter identification problems. These problems arise from the necessity of obtaining parameters of theoretical models in such a way that the models can be used to simulate the behaviour of the system for different operating conditions. Chapter 1 presents the parameter identification problem for power semiconductor models and chapter 2 for heat and mass transfer problems. Chapter 3 discusses the use of SA in radiotherapy treatment planning and presents recent work to apply SA in interstitial light therapies. The usefulness of solving an inverse problem is clear in this application: instead of manually specifying the treatment parameters and repeatedly evaluating the resulting radiation dose distribution, a desired dose distribution is prescribed by the physician and the task of finding the appropriate treatment parameters is automated with an optimisation algorithm.
Chapters 4 and 5 present two applications in Telecommunications field. Chapter 4 discusses the optimal design and formation of micromobility domains for extending location privacy protection capabilities of micromobility protocols. In chapter 5 SA is used for large-scale IP traffic matrix estimation, which is used by network operators to conduct network management, network planning and traffic detecting.
Chapter 6 and 7 present two SA applications in Geology and Molecular Biology fields, particularly the optimisation problem of land sampling schemes for land characterisation and primer design for PCR processes, respectively.
Some Electrical Engineering applications are analysed in chapters 8 to
11. Chapter 8 deals with network reconfiguration for reliability worth enhancement in electrical distribution systems. The optimal design of an interior permanent magnet motor for power steering applications is discussed in chapter
9. In chapter 10 SA is used for optimal control systems design and in chapter 11 for feature selection and dimensionality reduction for image classification tasks. Chapters 12 to 15 provide some depth to SA theory and comparative studies with other optimisation algorithms. There are several parameters in the process of annealing whose values affect the overall performance. Chapter 12 focuses on the initial temperature and proposes a new approach to set this control parameter. Chapter 13 presents improved approaches on the multilevel hierarchical floorplan/placement for large-scale circuits. An improved format of !-neighborhood and !-exchange algorithm in SA is used. In chapter 14 SA performance is compared with Steepest Ascent and Ant Colony Optimization as well as an hybridisation version. Control of adaptive optics system that compensates variations in the speed of light propagation is presented in last chapter. Here SA is also compared with Genetic Algorithm, Stochastic Parallel Gradient Descent and Algorithm of Patte extraction.
Parameter identification of power semiconductor device models using metaheuristics.
Application of simulated annealing and hybrid methods in the solution of inverse heat and mass transfer problems.
Towards conformal interstitial light therapies: Modelling parameters, dose definitions and computational implementation.
A Location Privacy Aware Network Planning Algorithm for Micromobility Protocols.
Simulated Annealing-Based Large-scale IP Traffic Matrix Estimation.
Field sampling scheme optimization using simulated annealing.
Customized Simulated Annealing Algorithm Suitable for Primer Design in Polymerase Chain Reaction Processes.
Network Reconfiguration for Reliability Worth Enhancement in Distribution System by Simulated Annealing.
Optimal Design of an IPM Motor for Electric Power Steering Application Using Simulated Annealing Method.
Using the simulated annealing algorithm to solve the optimal control problem.
A simulated annealing band selection approach for high-dimensional remote sensing images.
Importance of the initial conditions and the time schedule in the Simulated Annealing.
Multilevel Large-Scale Modules Floorplanning/Placement with Improved Neighborhood Exchange in Simulated Annealing.
Simulated Annealing and its Hybridisation on Noisy and Constrained Response Surface Optimisations.
Simulated Annealing for Control of Adaptive Optics System.