Simulated annealing

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Simulated annealing (SA) is a generic probabilistic metaheuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g. , all tours that visit a given set of cities). (Wikipedia.org)






Conferences related to Simulated annealing

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ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2019 IEEE International Electric Machines & Drives Conference (IEMDC)

The IEEE International Electric Machines and Drives Conference (IEMDC) has been established to be one of the major events in the field of electrical machines and drives. IEMDC is a refernce forum to disseminate and exchange state of art in the filed of the Electrical Machines and Drives. The 2018 edition started in 1997 and the 2019 edition will be 11th one.


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Periodicals related to Simulated annealing

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Antennas and Wireless Propagation Letters, IEEE

IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.


Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


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Most published Xplore authors for Simulated annealing

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Xplore Articles related to Simulated annealing

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Methods and algorithms for the design of proteins

IEE Colloquium on Molecular Bioinformatics, 1994

Protein design is a burgeoning new field of structural molecular biology, which entails selecting sequences of amino acids to fold into a desired pre- determined structure. The authors present a quantitative methodology for the de novo design of proteins as well as supporting algorithms, including a massively parallel simulated annealing optimization method. With these algorithms it is possible to choose ...


Simulated Annealing for Sequential Pattern Detection and Seismic Applications

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014

Sequential pattern detection with simulated annealing (SA) is adopted to estimate parameters and detect lines, ellipses, hyperbolas type by type, and patterns by patterns in each type. The motivation of the sequential detection method is to deal with multiple patterns. The parameters of a pattern are formed as a vector and used as a state, and adjusted in SA. A ...


A new approach to finite wordlength coefficient fir digital filter design using the branch and bound technique

2000 10th European Signal Processing Conference, 2000

It has been shown that the branch and bound technique is effective for the design of finite wordlength optimal digital filters. This technique is however expensive in computing time. In this paper, we present a robust branch and bound branching strategy named Sequential and Progressive Search, improving the design of filters on a large wordlength processor in a reasonable computing ...


Exploring design space using SAVAGE: a simulated annealing based VLSI architecture generator

Proceedings of the 33rd Midwest Symposium on Circuits and Systems, 1990

The authors present the prototype version of a synthesis system based around an architectural script design method. It is controlled by the computational technique known as simulated annealing. The system is exercized using a 5th order wave digital filter design.<<ETX>>


Grid Dependent Tasks Scheduling Based on Hybrid Adaptive Genetic Algorithm

2009 WRI Global Congress on Intelligent Systems, 2009

Dependent tasks scheduling in grid environment is a NP-complete problem. Convergence in the accuracy for conventional GA is better than other scheduling algorithms, but the speed of convergence is too slow in a realistic scheduling. In view of this situation, this paper presents a hybrid adaptive genetic algorithm (HAGA) which can improve the local search ability by adding the adjustment ...


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Educational Resources on Simulated annealing

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IEEE.tv Videos

An Ising Computer Based on Simulated Quantum Annealing by Path Integral Monte Carlo - IEEE Rebooting Computing 2017
Reducing Binary Quadratic Forms for More Scalable Quantum Annealing - IEEE Rebooting Computing 2017
Part 2: Workshop on Benchmarking Quantum Computational Devices and Systems - ICRC 2018
Development of Quantum Annealing Technology at D-Wave Systems - 2018 IEEE Industry Summit on the Future of Computing
Quantum Annealing: Current Status and Future Directions - Applied Superconductivity Conference 2018
Part 3: Workshop on Benchmarking Quantum Computational Devices and Systems - ICRC 2018
Leveraging Quantum Annealing for Large MIMO Processing - Kyle Jamieson - IEEE Sarnoff Symposium, 2019
Virtual World Symposium - Welcome Address
D-Wave Quantum Computer: Technology Update - Fabio Altomare - ICRC San Mateo, 2019
RF Power Amplifier Design for Pseudo Envelope Tracking
Lloyd Watts: Reverse-Engineering the Human Auditory Pathway -WCCI 2012 Plenary talk
A Recurrent Crossbar of Memristive Nanodevices Implements Online Novelty Detection - Christopher Bennett: 2016 International Conference on Rebooting Computing
Evaluating Over-The-Air Performance of MIMO Wireless Devices
Provably-Correct Robot Control with LTLMoP, OMPL and ROS
Micro-Apps 2013: Environment Simulation for Counter-IED Jammer Test
SDRJ: Small to Large Scale Quantum Computational Systems - Kae Nemoto at INC 2019
IEEE Magnetics Distinguished Lecture - Alison B. Flatau
Micro-Apps 2013: Design and Simulation of Phased Arrays in VSS
Gabriel Martins Dias: Using Data Prediction Techniques to Reduce Data Transmissions in the IoT: WF IoT 2016
IROS TV 2019-U.S. Military Academy, West Point- Robotics Research Center

IEEE-USA E-Books

  • Methods and algorithms for the design of proteins

    Protein design is a burgeoning new field of structural molecular biology, which entails selecting sequences of amino acids to fold into a desired pre- determined structure. The authors present a quantitative methodology for the de novo design of proteins as well as supporting algorithms, including a massively parallel simulated annealing optimization method. With these algorithms it is possible to choose sequences which should adopt an arbitrary plausible structure.<<ETX>>

  • Simulated Annealing for Sequential Pattern Detection and Seismic Applications

    Sequential pattern detection with simulated annealing (SA) is adopted to estimate parameters and detect lines, ellipses, hyperbolas type by type, and patterns by patterns in each type. The motivation of the sequential detection method is to deal with multiple patterns. The parameters of a pattern are formed as a vector and used as a state, and adjusted in SA. A sequential detection algorithm using SA to detect patterns is proposed. It detects one or a small number of patterns at each step. SA has the capability of the global minimization. The six parameters of patterns are adjusted sequentially step by step. The computation can converge efficiently. In the experiment, the result of sequential detection is better than that of synchronous detection in detecting a large number of patterns. In sequential detection, detection of one pattern at each step can have less computation time and good convergence in total detection than using two or more pattern detections. In simulated seismic data, SA is applied to detect the hyperbolas in the common depth point (CDP) gather. In real one-shot seismogram, SA is applied to detect lines of direct wave and hyperbolas of reflection wave. The results can show that the proposed method is feasible.

  • A new approach to finite wordlength coefficient fir digital filter design using the branch and bound technique

    It has been shown that the branch and bound technique is effective for the design of finite wordlength optimal digital filters. This technique is however expensive in computing time. In this paper, we present a robust branch and bound branching strategy named Sequential and Progressive Search, improving the design of filters on a large wordlength processor in a reasonable computing cost. The details of the algorithm and many examples are given and compared to the other methods.

  • Exploring design space using SAVAGE: a simulated annealing based VLSI architecture generator

    The authors present the prototype version of a synthesis system based around an architectural script design method. It is controlled by the computational technique known as simulated annealing. The system is exercized using a 5th order wave digital filter design.<<ETX>>

  • Grid Dependent Tasks Scheduling Based on Hybrid Adaptive Genetic Algorithm

    Dependent tasks scheduling in grid environment is a NP-complete problem. Convergence in the accuracy for conventional GA is better than other scheduling algorithms, but the speed of convergence is too slow in a realistic scheduling. In view of this situation, this paper presents a hybrid adaptive genetic algorithm (HAGA) which can improve the local search ability by adding the adjustment for the specific problem, so it has good global and local search ability. At the same time, in order to avoid such disadvantages as premature convergence, low convergence speed and low stability, the algorithm adjusts the crossover and mutation probability adaptively and nonlinearly. Experiments show that the presented algorithm not only improves the speed of convergence, but also improves the accuracy of convergence.

  • A flexible clustering and floor planning approach to standard cell placement using hierarchical simulated annealing

    Conventional simulated annealing algorithm, which works on the flattened circuit, has a very large search space and hence requires a huge computational effort. In this research, a hierarchical strategy was established. The placement problem is divided into three sub-problems: clustering, floorplanning and final placement. This research is different from a previous work, which used similar strategy, allowing clusters to occupy more than one row and have variable aspect-ratio in the stage of floorplanning. The sub- tasks of clustering and floorplanning could be finished with small amount of CPU time. The sub-task of final placement was done by modified version of the well-known TimberWolfSC program. It was found that, as a consequence of the hierarchical approach, the search-efficiency of the final placement is improved significantly over the conventional non-hierarchical approach.<<ETX>>

  • Laser Antimissile Optimization Based on Very Fast Simulated Annealing Algorithm

    The dynamic laser antimissile problem is focused on with the very fast simulated annealing (VFSA) algorithm. The attacking ordering optimization plays an important role in the real-time application. This problem is much harder than the traveling salesman problem. There are many barriers for finding the global optimal solution, especially when the number of the targets is greater than six. The very fast simulated annealing algorithm is introduced here. And the fast simulated annealing (FSA) and classical simulated annealing (CSA) are also used to compare with the VFSA. Finally, taking ten targets as an example, the simulation results show that VFSA has faster convergence than those of the CSA and FSA. Therefore, the VFSA can be used in real-word application.

  • Optimizing strategy for MR imaging gradient coils

    An optimization technique for magnetic resonance imaging gradient coils is presented. Assuming the coil in the form of four windings, each having a spiral polygon shape, the coordinates of nodes are varied to optimize the coil performance. The hybrid simulated annealing - Powell technique is used as the numerical tool. Results of calculations for differently formulated goal functions are demonstrated.<<ETX>>

  • VFSR trained artificial neural networks

    Artificial neural networks are most often trained using backward error propagation (BEP), which works quite well for network training problems having a single minimum in the error function. Although BEP has been successful in many applications, there can be substantial problems in convergence because of the existence of local minima and network paralysis. We describe a method for avoiding local minima by combining very fast simulated reannealing (VFSR) with BEP. While convergence to the best training weights can be slower than gradient descent methods, it is faster than other SA network training methods. More importantly, convergence to the optimal weight set is guaranteed. We demonstrate VFSR network training on a variety of test problems, such as the exclusive-or and parity problems, and compare performances of VFSR network training with conjugate gradient trained backpropagation networks.

  • Chaotic noise and iterative simulated annealing for TSP

    We investigate the solving ability of TSP by using a Hopfield neural network with chaotic noise and iterative simulated annealing noise. From several numerical experiments, we can conclude that the ability of iterative simulated annealing noise is almost the same as chaotic noise in searching ability of a global minimum, and is superior to the chaotic noise in performance for detecting local minima.



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