Adaptive simulated annealing (ASA): Lessons learned
Ingber, L.
2000-01-01
Adaptive simulated annealing (ASA) is a global optimization algorithm based on an associated proof that the parameter space can be sampled much more efficiently than by using other previous simulated annealing algorithms. The author's ASA code has been publicly available for over two years. During this time the author has volunteered to help people via e-mail, and the feedback obtained has been used to further develop the code. Some lessons learned, in particular some which are relevant to ot...
Adaptive Simulated Annealing Based Protein Loop Modeling of Neurotoxins
陈杰; 黄丽娜; 彭志红
2003-01-01
A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interface-friendly toolbox-LoopModeller in Windows and Linux systems, VC++ and OpenGL environments is developed for analysis and visualization. Simulation results of three short-chain neurotoxins modeled by LoopModeller show that the method proposed is fast and efficient.
Sheng, Zheng, E-mail: 19994035@sina.com [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Wang, Jun; Zhou, Bihua [National Defense Key Laboratory on Lightning Protection and Electromagnetic Camouflage, PLA University of Science and Technology, Nanjing 210007 (China); Zhou, Shudao [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 (China)
2014-03-15
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua
2014-03-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Simulated annealing versus quantum annealing
Troyer, Matthias
Based on simulated classical annealing and simulated quantum annealing using quantum Monte Carlo (QMC) simulations I will explore the question where physical or simulated quantum annealers may outperform classical optimization algorithms. Although the stochastic dynamics of QMC simulations is not the same as the unitary dynamics of a quantum system, I will first show that for the problem of quantum tunneling between two local minima both QMC simulations and a physical system exhibit the same scaling of tunneling times with barrier height. The scaling in both cases is O (Δ2) , where Δ is the tunneling splitting. An important consequence is that QMC simulations can be used to predict the performance of a quantum annealer for tunneling through a barrier. Furthermore, by using open instead of periodic boundary conditions in imaginary time, equivalent to a projector QMC algorithm, one obtains a quadratic speedup for QMC, and achieve linear scaling in Δ. I will then address the apparent contradiction between experiments on a D-Wave 2 system that failed to see evidence of quantum speedup and previous QMC results that indicated an advantage of quantum annealing over classical annealing for spin glasses. We find that this contradiction is resolved by taking the continuous time limit in the QMC simulations which then agree with the experimentally observed behavior and show no speedup for 2D spin glasses. However, QMC simulations with large time steps gain further advantage: they ``cheat'' by ignoring what happens during a (large) time step, and can thus outperform both simulated quantum annealers and classical annealers. I will then address the question how to optimally run a simulated or physical quantum annealer. Investigating the behavior of the tails of the distribution of runtimes for very hard instances we find that adiabatically slow annealing is far from optimal. On the contrary, many repeated relatively fast annealing runs can be orders of magnitude faster for
Ry, Rexha Verdhora, E-mail: rexha.vry@gmail.com [Master Program of Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jalan Ganesha No.10, Bandung 40132 (Indonesia); Nugraha, Andri Dian, E-mail: nugraha@gf.itb.ac.id [Global Geophysical Research Group, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jalan Ganesha No.10, Bandung 40132 (Indonesia)
2015-04-24
Observation of earthquakes is routinely used widely in tectonic activity observation, and also in local scale such as volcano tectonic and geothermal activity observation. It is necessary for determining the location of precise hypocenter which the process involves finding a hypocenter location that has minimum error between the observed and the calculated travel times. When solving this nonlinear inverse problem, simulated annealing inversion method can be applied to such global optimization problems, which the convergence of its solution is independent of the initial model. In this study, we developed own program codeby applying adaptive simulated annealing inversion in Matlab environment. We applied this method to determine earthquake hypocenter using several data cases which are regional tectonic, volcano tectonic, and geothermal field. The travel times were calculated using ray tracing shooting method. We then compared its results with the results using Geiger’s method to analyze its reliability. Our results show hypocenter location has smaller RMS error compared to the Geiger’s result that can be statistically associated with better solution. The hypocenter of earthquakes also well correlated with geological structure in the study area. Werecommend using adaptive simulated annealing inversion to relocate hypocenter location in purpose to get precise and accurate earthquake location.
Observation of earthquakes is routinely used widely in tectonic activity observation, and also in local scale such as volcano tectonic and geothermal activity observation. It is necessary for determining the location of precise hypocenter which the process involves finding a hypocenter location that has minimum error between the observed and the calculated travel times. When solving this nonlinear inverse problem, simulated annealing inversion method can be applied to such global optimization problems, which the convergence of its solution is independent of the initial model. In this study, we developed own program codeby applying adaptive simulated annealing inversion in Matlab environment. We applied this method to determine earthquake hypocenter using several data cases which are regional tectonic, volcano tectonic, and geothermal field. The travel times were calculated using ray tracing shooting method. We then compared its results with the results using Geiger’s method to analyze its reliability. Our results show hypocenter location has smaller RMS error compared to the Geiger’s result that can be statistically associated with better solution. The hypocenter of earthquakes also well correlated with geological structure in the study area. Werecommend using adaptive simulated annealing inversion to relocate hypocenter location in purpose to get precise and accurate earthquake location
The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. Finally, our simulated annealing program
Adaptive MANET Multipath Routing Algorithm Based on the Simulated Annealing Approach
Sungwook Kim
2014-01-01
Full Text Available Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.
Iglesias-Marzoa, Ramón; Morales, María Jesús Arévalo
2015-01-01
The fitting of radial velocity curves is a frequent procedure in binary stars and exoplanet research. In the majority of cases the fitting routines need to be fed with a set of initial parameter values and priors from which to begin the computations and their results can be affected by local minima. We present a new code, the rvfit code, for fitting radial velocities of stellar binaries and exoplanets using an Adaptive Simulated Annealing (ASA) global minimization method, which fastly converges to a global solution minimum without the need to provide preliminary parameter values. We show the performance of the code using both synthetic and real data sets: double-lined binaries, single-lined binaries, and exoplanet systems. In all examples the keplerian orbital parameters fitted by the rvfit code and their computed uncertainties are compared with literature solutions. Finally, we provide the source code with a working example and a detailed description on how to use it.
Generalized Simulated Annealing
Tsallis, Constantino; Stariolo, Daniel A.
1995-01-01
We propose a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so called classical ("Boltzmann machine") and fast ("Cauchy machine") simulated annealings, and can be quicker than both. Key-words: simulated annealing; nonconvex optimization; gradient descent; generalized statistical mechan...
姚新; 李国杰
1991-01-01
Simulated annealing is a new kind of random search methods developed in recent years.It can also be considered as an extension to the classical hill-climbing method in AI--probabilistic hill-cimbing.One of its most important features is its global convergence.The convergence of simulated annealing algorithm is determined by state generating probability,state accepting probability,and temperature decreasing rate,This paper gives a generalized simulated annealing algorithm with dynamic generating and accepting probabilities.The paper also shows that the generating and accepting probabilities can adopt many different kinds of distributions while the global convergence is guaranteed.
Keystream Generator Based On Simulated Annealing
Ayad A. Abdulsalam
2011-01-01
Full Text Available Advances in the design of keystream generator using heuristic techniques are reported. A simulated annealing algorithm for generating random keystream with large complexity is presented. Simulated annealing technique is adapted to locate these requirements. The definitions for some cryptographic properties are generalized, providing a measure suitable for use as an objective function in a simulated annealing algorithm, seeking randomness that satisfy both correlation immunity and the large linear complexity. Results are presented demonstrating the effectiveness of the method.
On lumped models for thermodynamic properties of simulated annealing problems
Andresen, Bjarne; Hoffmann, Karl Heinz; Mosegaard, Klaus; Nulton, Jim; Pedersen, Jacob Mørch; Salamon, Peter
1988-01-01
The paper describes a new method for the estimation of thermodynamic properties for simulated annealing problems using data obtained during a simulated annealing run. The method works by estimating energy-to-energy transition probabilities and is well adapted to simulations such as simulated annealing, in which the system is never in equilibrium.
multicast utilizando Simulated Annealing
Yezid Donoso
2005-01-01
Full Text Available En este artículo se presenta un método de optimización multiobjetivo para la solución del problema de balanceo de carga en redes de transmisión multicast, apoyándose en la aplicación de la meta-heurística de Simulated Annealing (Recocido Simulado. El método minimiza cuatro parámetros básicos para garantizar la calidad de servicio en transmisiones multicast: retardo origen destino, máxima utilización de enlaces, ancho de banda consumido y número de saltos. Los resultados devueltos por la heurística serán comparados con los resultados arrojados por el modelo matemático propuesto en investigaciones anteriores.
Implementation of a Simulated Annealing algorithm for Matlab
Moins, Stephane
2002-01-01
In this report we describe an adaptive simulated annealing method for sizing the devices in analog circuits. The motivation for use an adaptive simulated annealing method for analog circuit design are to increase the efficiency of the design circuit. To demonstrate the functionality and the performance of the approach, an operational transconductance amplifier is simulated. The circuit is modeled with symbolic equations that are derived automatically by a simulator.
Recursive simulation of quantum annealing
The evaluation of the performance of adiabatic annealers is hindered by the lack of efficient algorithms for simulating their behaviour. We exploit the analyticity of the standard model for the adiabatic quantum process to develop an efficient recursive method for its numerical simulation in case of both unitary and non-unitary evolution. Numerical simulations show distinctly different distributions for the most important figure of merit of adiabatic quantum computing—the success probability—in these two cases. (paper)
Recursive simulation of quantum annealing
Sowa, A P; Samson, J H; Savel'ev, S E; Zagoskin, A M; Heidel, S; Zúñiga-Anaya, J C
2015-01-01
The evaluation of the performance of adiabatic annealers is hindered by lack of efficient algorithms for simulating their behaviour. We exploit the analyticity of the standard model for the adiabatic quantum process to develop an efficient recursive method for its numerical simulation in case of both unitary and non-unitary evolution. Numerical simulations show distinctly different distributions for the most important figure of merit of adiabatic quantum computing --- the success probability --- in these two cases.
Simulation of Storm Occurrences Using Simulated Annealing.
Lokupitiya, Ravindra S.; Borgman, Leon E.; Anderson-Sprecher, Richard
2005-11-01
Modeling storm occurrences has become a vital part of hurricane prediction. In this paper, a method for simulating event occurrences using a simulated annealing algorithm is described. The method is illustrated using annual counts of hurricanes and of tropical storms in the Atlantic Ocean and Gulf of Mexico. Simulations closely match distributional properties, including possible correlations, in the historical data. For hurricanes, traditionally used Poisson and negative binomial processes also predict univariate properties well, but for tropical storms parametric methods are less successful. The authors determined that simulated annealing replicates properties of both series. Simulated annealing can be designed so that simulations mimic historical distributional properties to whatever degree is desired, including occurrence of extreme events and temporal patterning.
Using Simulated Annealing to Factor Numbers
Altschuler, Eric Lewin; Williams, Timothy J.
2014-01-01
Almost all public secure communication relies on the inability to factor large numbers. There is no known analytic or classical numeric method to rapidly factor large numbers. Shor[1] has shown that a quantum computer can factor numbers in polynomial time but there is no practical quantum computer that can yet do such computations. We show that a simulated annealing[2] approach can be adapted to find factors of large numbers.
Berthiau, G.
1995-10-01
The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. (Abstract Truncated)
Feasibility of Simulated Annealing Tomography
Vo, Nghia T; Moser, Herbert O
2014-01-01
Simulated annealing tomography (SAT) is a simple iterative image reconstruction technique which can yield a superior reconstruction compared with filtered back-projection (FBP). However, the very high computational cost of iteratively calculating discrete Radon transform (DRT) has limited the feasibility of this technique. In this paper, we propose an approach based on the pre-calculated intersection lengths array (PILA) which helps to remove the step of computing DRT in the simulated annealing procedure and speed up SAT by over 300 times. The enhancement of convergence speed of the reconstruction process using the best of multiple-estimate (BoME) strategy is introduced. The performance of SAT under different conditions and in comparison with other methods is demonstrated by numerical experiments.
Recursive Branching Simulated Annealing Algorithm
Bolcar, Matthew; Smith, J. Scott; Aronstein, David
2012-01-01
This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal
Very Fast Simulated Re-Annealing
Ingber, Lester
1989-01-01
Draft An algorithm is developed to statistically find the best global fit of a nonlinear non-convex cost-function over a D-dimensional space. It is argued that this algorithm permits an annealing schedule for ‘‘temperature’’ T decreasing exponentially in annealing-time k, T = T0 exp(−ck1/D). The introduction of re-annealing also permits adaptation to changing sensitivities in the multidimensional parameter-space. This annealing schedule is faster than fast Cauchy annealing, ...
NEW SIMULATED ANNEALING ALGORITHMS FOR CONSTRAINED OPTIMIZATION
LINET ÖZDAMAR; CHANDRA SEKHAR PEDAMALLU
2010-01-01
We propose a Population based dual-sequence Non-Penalty Annealing algorithm (PNPA) for solving the general nonlinear constrained optimization problem. The PNPA maintains a population of solutions that are intermixed by crossover to supply a new starting solution for simulated annealing throughout the search. Every time the search gets stuck at a local optimum, this crossover procedure is triggered and simulated annealing search re-starts from a new subspace. In both the crossover and simulate...
Quantum annealing speedup over simulated annealing on random Ising chains
Zanca, Tommaso
2015-01-01
We show clear evidence of a speedup of a quantum annealing (QA) Schr\\"odinger dynamics over a Glauber master-equation simulated annealing (SA) for a random Ising model in one dimension. Annealings are tackled on equal footing, by a deterministic dynamics of the resulting Jordan-Wigner fermionic problems. We find that disorder, without frustration, makes both SA and real-time QA logarithmically slow in the annealing time $\\tau$, but QA shows a quadratic speedup with respect to SA. We also find that an imaginary-time Schr\\"odinger QA dynamics provides a further exponential speedup, with an asymptotic residual error compatible with a power-law $\\tau^{-\\mu}$.
Simulated Annealing using Hybrid Monte Carlo
Salazar, Rafael; Toral, Raúl
1997-01-01
We propose a variant of the simulated annealing method for optimization in the multivariate analysis of differentiable functions. The method uses global actualizations via the hybrid Monte Carlo algorithm in their generalized version for the proposal of new configurations. We show how this choice can improve upon the performance of simulated annealing methods (mainly when the number of variables is large) by allowing a more effective searching scheme and a faster annealing schedule.
Cylinder packing by simulated annealing
M. Helena Correia
2000-12-01
Full Text Available This paper is motivated by the problem of loading identical items of circular base (tubes, rolls, ... into a rectangular base (the pallet. For practical reasons, all the loaded items are considered to have the same height. The resolution of this problem consists in determining the positioning pattern of the circular bases of the items on the rectangular pallet, while maximizing the number of items. This pattern will be repeated for each layer stacked on the pallet. Two algorithms based on the meta-heuristic Simulated Annealing have been developed and implemented. The tuning of these algorithms parameters implied running intensive tests in order to improve its efficiency. The algorithms developed were easily extended to the case of non-identical circles.Este artigo aborda o problema de posicionamento de objetos de base circular (tubos, rolos, ... sobre uma base retangular de maiores dimensões. Por razões práticas, considera-se que todos os objetos a carregar apresentam a mesma altura. A resolução do problema consiste na determinação do padrão de posicionamento das bases circulares dos referidos objetos sobre a base de forma retangular, tendo como objetivo a maximização do número de objetos estritamente posicionados no interior dessa base. Este padrão de posicionamento será repetido em cada uma das camadas a carregar sobre a base retangular. Apresentam-se dois algoritmos para a resolução do problema. Estes algoritmos baseiam-se numa meta-heurística, Simulated Annealling, cuja afinação de parâmetros requereu a execução de testes intensivos com o objetivo de atingir um elevado grau de eficiência no seu desempenho. As características dos algoritmos implementados permitiram que a sua extensão à consideração de círculos com raios diferentes fosse facilmente conseguida.
Quantum annealing speedup over simulated annealing on random Ising chains
Zanca, Tommaso; Santoro, Giuseppe E.
2016-06-01
We show clear evidence of a quadratic speedup of a quantum annealing (QA) Schrödinger dynamics over a Glauber master equation simulated annealing (SA) for a random Ising model in one dimension, via an equal-footing exact deterministic dynamics of the Jordan-Wigner fermionized problems. This is remarkable, in view of the arguments of H. G. Katzgraber et al. [Phys. Rev. X 4, 021008 (2014), 10.1103/PhysRevX.4.021008], since SA does not encounter any phase transition, while QA does. We also find a second remarkable result: that a "quantum-inspired" imaginary-time Schrödinger QA provides a further exponential speedup, i.e., an asymptotic residual error decreasing as a power law τ-μ of the annealing time τ .
Classical Simulated Annealing Using Quantum Analogues
La Cour, Brian R.; Troupe, James E.; Mark, Hans M.
2016-08-01
In this paper we consider the use of certain classical analogues to quantum tunneling behavior to improve the performance of simulated annealing on a discrete spin system of the general Ising form. Specifically, we consider the use of multiple simultaneous spin flips at each annealing step as an analogue to quantum spin coherence as well as modifications of the Boltzmann acceptance probability to mimic quantum tunneling. We find that the use of multiple spin flips can indeed be advantageous under certain annealing schedules, but only for long anneal times.
Classical Simulated Annealing Using Quantum Analogues
La Cour, Brian R.; Troupe, James E.; Mark, Hans M.
2016-06-01
In this paper we consider the use of certain classical analogues to quantum tunneling behavior to improve the performance of simulated annealing on a discrete spin system of the general Ising form. Specifically, we consider the use of multiple simultaneous spin flips at each annealing step as an analogue to quantum spin coherence as well as modifications of the Boltzmann acceptance probability to mimic quantum tunneling. We find that the use of multiple spin flips can indeed be advantageous under certain annealing schedules, but only for long anneal times.
Simulated Quantum Annealing Can Be Exponentially Faster than Classical Simulated Annealing
Crosson, Elizabeth; Harrow, Aram W.
2016-01-01
Simulated Quantum Annealing (SQA) is a Markov Chain Monte-Carlo algorithm that samples the equilibrium thermal state of a Quantum Annealing (QA) Hamiltonian. In addition to simulating quantum systems, SQA has also been proposed as another physics-inspired classical algorithm for combinatorial optimization, alongside classical simulated annealing. However, in many cases it remains an open challenge to determine the performance of both QA and SQA. One piece of evidence for the strength of Q...
An Introduction to Simulated Annealing
Albright, Brian
2007-01-01
An attempt to model the physical process of annealing lead to the development of a type of combinatorial optimization algorithm that takes on the problem of getting trapped in a local minimum. The author presents a Microsoft Excel spreadsheet that illustrates how this works.
Stochastic annealing simulation of cascades in metals
Heinisch, H.L.
1996-04-01
The stochastic annealing simulation code ALSOME is used to investigate quantitatively the differential production of mobile vacancy and SIA defects as a function of temperature for isolated 25 KeV cascades in copper generated by MD simulations. The ALSOME code and cascade annealing simulations are described. The annealing simulations indicate that the above Stage V, where the cascade vacancy clusters are unstable,m nearly 80% of the post-quench vacancies escape the cascade volume, while about half of the post-quench SIAs remain in clusters. The results are sensitive to the relative fractions of SIAs that occur in small, highly mobile clusters and large stable clusters, respectively, which may be dependent on the cascade energy.
Constrained multi-global optimization using a penalty stretched simulated annealing framework
Pereira, Ana I.; Edite M.G.P. Fernandes
2009-01-01
This paper presents a new simulated annealing algorithm to solve constrained multi-global optimization problems. To compute all global solutions in a sequential manner, we combine the function stretching technique with the adaptive simulated annealing variant. Constraint-handling is carried out through a nondifferentiable penalty function. To benchmark our penalty stretched simulated annealing algorithm we solve a set of well-known problems. Our preliminary numerical results show that the alg...
Hierarchical Network Design Using Simulated Annealing
Thomadsen, Tommy; Clausen, Jens
2002-01-01
networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub...
Parallel simulated annealing algorithms for cell placement on hypercube multiprocessors
Banerjee, Prithviraj; Jones, Mark Howard; Sargent, Jeff S.
1990-01-01
Two parallel algorithms for standard cell placement using simulated annealing are developed to run on distributed-memory message-passing hypercube multiprocessors. The cells can be mapped in a two-dimensional area of a chip onto processors in an n-dimensional hypercube in two ways, such that both small and large cell exchange and displacement moves can be applied. The computation of the cost function in parallel among all the processors in the hypercube is described, along with a distributed data structure that needs to be stored in the hypercube to support the parallel cost evaluation. A novel tree broadcasting strategy is used extensively for updating cell locations in the parallel environment. A dynamic parallel annealing schedule estimates the errors due to interacting parallel moves and adapts the rate of synchronization automatically. Two novel approaches in controlling error in parallel algorithms are described: heuristic cell coloring and adaptive sequence control.
Code Generator for Quantum Simulated Annealing
Tucci, Robert R
2009-01-01
This paper introduces QuSAnn v1.2 and Multiplexor Expander v1.2, two Java applications available for free. (Source code included in the distribution.) QuSAnn is a "code generator" for quantum simulated annealing: after the user inputs some parameters, it outputs a quantum circuit for performing simulated annealing on a quantum computer. The quantum circuit implements the algorithm of Wocjan et al. (arXiv:0804.4259), which improves on the original algorithm of Somma et al. (arXiv:0712.1008). The quantum circuit generated by QuSAnn includes some quantum multiplexors. The application Multiplexor Expander allows the user to replace each of those multiplexors by a sequence of more elementary gates such as multiply controlled NOTs and qubit rotations.
Learning FCM by chaotic simulated annealing
Fuzzy cognitive map (FCM) is a directed graph, which shows the relations between essential components in complex systems. It is a very convenient, simple, and powerful tool, which is used in numerous areas of application. Experts who are familiar with the system components and their relations can generate a related FCM. There is a big gap when human experts cannot produce FCM or even there is no expert to produce the related FCM. Therefore, a new mechanism must be used to bridge this gap. In this paper, a novel learning method is proposed to construct FCM by using Chaotic simulated annealing (CSA). The proposed method not only is able to construct FCM graph topology but also is able to extract the weight of the edges from input historical data. The efficiency of the proposed method is shown via comparison of its results of some numerical examples with those of Simulated annealing (SA) method.
Simulated annealing in orbital flight planning
Soller, Jeffrey
1990-01-01
Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.
Simulated Annealing with Tsallis Weights - A Numerical Comparison
Hansmann, Ulrich H.E.
1997-01-01
We discuss the use of Tsallis generalized mechanics in simulated annealing algorithms. For a small peptide it is shown that older implementations are not more effective than regular simulated annealing in finding ground state configurations. We propose a new implementation which leads to an improvement over regular simulated annealing.
Solving maximum cut problems by simulated annealing
Myklebust, Tor G. J.
2015-01-01
This paper gives a straightforward implementation of simulated annealing for solving maximum cut problems and compares its performance to that of some existing heuristic solvers. The formulation used is classical, dating to a 1989 paper of Johnson, Aragon, McGeoch, and Schevon. This implementation uses no structure peculiar to the maximum cut problem, but its low per-iteration cost allows it to find better solutions than were previously known for 40 of the 89 standard maximum cut instances te...
MEDICAL STAFF SCHEDULING USING SIMULATED ANNEALING
Ladislav Rosocha; Silvia Vernerova; Robert Verner
2015-01-01
Purpose: The efficiency of medical staff is a fundamental feature of healthcare facilities quality. Therefore the better implementation of their preferences into the scheduling problem might not only rise the work-life balance of doctors and nurses, but also may result into better patient care. This paper focuses on optimization of medical staff preferences considering the scheduling problem. Methodology/Approach: We propose a medical staff scheduling algorithm based on simulated annealing, a...
MEDICAL STAFF SCHEDULING USING SIMULATED ANNEALING
Ladislav Rosocha; Silvia Vernerova; Robert Verner
2015-01-01
Purpose: The efficiency of medical staff is a fundamental feature of healthcare facilities quality. Therefore the better implementation of their preferences into the scheduling problem might not only rise the work-life balance of doctors and nurses, but also may result into better patient care. This paper focuses on optimization of medical staff preferences considering the scheduling problem.Methodology/Approach: We propose a medical staff scheduling algorithm based on simulated annealing, a ...
Binary Sparse Phase Retrieval via Simulated Annealing
Wei Peng
2016-01-01
Full Text Available This paper presents the Simulated Annealing Sparse PhAse Recovery (SASPAR algorithm for reconstructing sparse binary signals from their phaseless magnitudes of the Fourier transform. The greedy strategy version is also proposed for a comparison, which is a parameter-free algorithm. Sufficient numeric simulations indicate that our method is quite effective and suggest the binary model is robust. The SASPAR algorithm seems competitive to the existing methods for its efficiency and high recovery rate even with fewer Fourier measurements.
Reactor controller design using genetic algorithms with simulated annealing
This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)
Hypocoercivity in metastable settings and kinetic simulated annealing
Monmarché, Pierre
2015-01-01
Classical analysis of the simulated annealing algorithm is combined with the more recent hypocoercive method of distorted entropy to prove the convergence for large time of the kinetic Langevin annealing with logarithmic cooling schedule.
Simulated annealing algorithm for detecting graph isomorphism
Geng Xiutang; Zhang Kai
2008-01-01
Evolutionary computation techniques have mostly been used to solve various optimization problems,and it is well known that graph isomorphism problem (GIP) is a nondeterministic polynomial problem.A simulated annealing (SA) algorithm for detecting graph isomorphism is proposed,and the proposed SA algorithm is well suited to deal with random graphs with large size.To verify the validity of the proposed SA algorithm,simulations are performed on three pairs of small graphs and four pairs of large random graphs with edge densities 0.5,0.1,and 0.01,respectively.The simulation results show that the proposed SA algorithm can detect graph isomorphism with a high probability.
Simulated Annealing of Two Electron Density Solution Systems
Neto, Mario de Oliveira; Alonso, Ronaldo Luiz; Leite, Fabio Lima; Jr, Osvaldo N. Oliveira; Polikarpov, Igor; Mascarenhas, Yvonne Primerano
2008-01-01
Many structural studies have been performed with a combination of SAXS and simulated annealing to reconstruct three dimensional models. Simulated annealing is suitable for the study of monodisperse, diluted and two-electron densities systems. In this chapter we showed how the simulated annealing procedure can be used to minimize the discrepancy between two functions: the simulated intensity and the experimental one-dimensional SAXS curve. The goal was to find the most probable form for a prot...
MEDICAL STAFF SCHEDULING USING SIMULATED ANNEALING
Ladislav Rosocha
2015-07-01
Full Text Available Purpose: The efficiency of medical staff is a fundamental feature of healthcare facilities quality. Therefore the better implementation of their preferences into the scheduling problem might not only rise the work-life balance of doctors and nurses, but also may result into better patient care. This paper focuses on optimization of medical staff preferences considering the scheduling problem.Methodology/Approach: We propose a medical staff scheduling algorithm based on simulated annealing, a well-known method from statistical thermodynamics. We define hard constraints, which are linked to legal and working regulations, and minimize the violations of soft constraints, which are related to the quality of work, psychic, and work-life balance of staff.Findings: On a sample of 60 physicians and nurses from gynecology department we generated monthly schedules and optimized their preferences in terms of soft constraints. Our results indicate that the final value of objective function optimized by proposed algorithm is more than 18-times better in violations of soft constraints than initially generated random schedule that satisfied hard constraints.Research Limitation/implication: Even though the global optimality of final outcome is not guaranteed, desirable solutionwas obtained in reasonable time. Originality/Value of paper: We show that designed algorithm is able to successfully generate schedules regarding hard and soft constraints. Moreover, presented method is significantly faster than standard schedule generation and is able to effectively reschedule due to the local neighborhood search characteristics of simulated annealing.
Measures of Fault Tolerance in Distributed Simulated Annealing
Prakash, Aaditya
2012-01-01
In this paper, we examine the different measures of Fault Tolerance in a Distributed Simulated Annealing process. Optimization by Simulated Annealing on a distributed system is prone to various sources of failure. We analyse simulated annealing algorithm, its architecture in distributed platform and potential sources of failures. We examine the behaviour of tolerant distributed system for optimization task. We present possible methods to overcome the failures and achieve fault tolerance for t...
A Parallel Genetic Simulated Annealing Hybrid Algorithm for Task Scheduling
SHU Wanneng; ZHENG Shijue
2006-01-01
In this paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing hybrid algorithm (PGSAHA) and applied to solve task scheduling problem in grid computing .It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively.When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole.From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.
Simulation of annealed polyelectrolytes in poor solvents
We present (semi-)grand canonical Monte Carlo simulations on annealed polyelectrolytes in poor solvent. Increasing the chemical potential of the charges, which is equal to the pH of the solution except for a trivial additive constant, in rather poor solvents, we find the first-order phase transition between a weakly charged globule and a highly charged extended chain predicted by theory. In the close-to-Q -point regime, we investigate under which conditions pearl-necklace structures are stable. Most of the pearl-necklace parameters are found to obey the scaling relations predicted for quenched polyelectrolytes. However, similarly to the behavior known for this class of polyelectrolytes we obtain large fluctuations in pearl number and size. In agreement with theoretical predictions we find a non-uniform charge distribution between pearls and strings
Tunneling through high energy barriers in simulated quantum annealing
Crosson, Elizabeth; Deng, Mingkai
2014-01-01
We analyze the performance of simulated quantum annealing (SQA) on an optimization problem for which simulated classical annealing (SA) is provably inefficient because of a high energy barrier. We present evidence that SQA can pass through this barrier to find the global minimum efficiently. This demonstrates the potential for SQA to inherit some of the advantages of quantum annealing (QA), since this problem has been previously shown to be efficiently solvable by quantum adiabatic optimization.
Simulated Annealing for Location Area Planning in Cellular networks
Prajapati, N. B.; R. R. Agravat; Hasan, M I
2010-01-01
LA planning in cellular network is useful for minimizing location management cost in GSM network. In fact, size of LA can be optimized to create a balance between the LA update rate and expected paging rate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithm is used. Simulated annealing give optimal results in acceptable run-time.
Simulated Annealing for Location Area Planning in Cellular networks
N. B. Prajapati
2010-03-01
Full Text Available LA planning in cellular network is useful for minimizing location management cost in GSM network. Infact, size of LA can be optimized to create a balance between the LA update rate and expected pagingrate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithmis used. Simulated annealing give optimal results in acceptable run-time.
Remote sensing of atmospheric duct parameters using simulated annealing
Zhao Xiao-Feng; Huang Si-Xun; Xiang Jie; Shi Wei-Lai
2011-01-01
Simulated annealing is one of the robust optimization schemes. Simulated annealing mimics the annealing process of the slow cooling of a heated metal to reach a stable minimum energy state. In this paper,we adopt simulated annealing to study the problem of the remote sensing of atmospheric duct parameters for two different geometries of propagation measurement. One is from a single emitter to an array of radio receivers (vertical measurements),and the other is from the radar clutter returns (horizontal measurements). Basic principles of simulated annealing and its applications to refractivity estimation are introduced. The performance of this method is validated using numerical experiments and field measurements collected at the East China Sea. The retrieved results demonstrate the feasibility of simulated annealing for near real-time atmospheric refractivity estimation. For comparison,the retrievals of the genetic algorithm are also presented. The comparisons indicate that the convergence speed of simulated annealing is faster than that of the genetic algorithm,while the anti-noise ability of the genetic algorithm is better than that of simulated annealing.
Simulated annealing with probabilistic analysis for solving traveling salesman problems
Hong, Pei-Yee; Lim, Yai-Fung; Ramli, Razamin; Khalid, Ruzelan
2013-09-01
Simulated Annealing (SA) is a widely used meta-heuristic that was inspired from the annealing process of recrystallization of metals. Therefore, the efficiency of SA is highly affected by the annealing schedule. As a result, in this paper, we presented an empirical work to provide a comparable annealing schedule to solve symmetric traveling salesman problems (TSP). Randomized complete block design is also used in this study. The results show that different parameters do affect the efficiency of SA and thus, we propose the best found annealing schedule based on the Post Hoc test. SA was tested on seven selected benchmarked problems of symmetric TSP with the proposed annealing schedule. The performance of SA was evaluated empirically alongside with benchmark solutions and simple analysis to validate the quality of solutions. Computational results show that the proposed annealing schedule provides a good quality of solution.
Surface Structure of Hydroxyapatite from Simulated Annealing Molecular Dynamics Simulations.
Wu, Hong; Xu, Dingguo; Yang, Mingli; Zhang, Xingdong
2016-05-10
The surface structure of hydroxyapatite (HAP) is crucial for its bioactivity. Using a molecular dynamics simulated annealing method, we studied the structure and its variation with annealing temperature of the HAP (100) surface. In contrast to the commonly used HAP surface model, which is sliced from HAP crystal and then relaxed at 0 K with first-principles or force-field calculations, a new surface structure with gradual changes from ordered inside to disordered on the surface was revealed. The disordering is dependent on the annealing temperature, Tmax. When Tmax increases up to the melting point, which was usually adopted in experiments, the disordering increases, as reflected by its radial distribution functions, structural factors, and atomic coordination numbers. The disordering of annealed structures does not show significant changes when Tmax is above the melting point. The thickness of disordered layers is about 10 Å. The surface energy of the annealed structures at high temperature is significantly less than that of the crystal structure relaxed at room temperature. A three-layer model of interior, middle, and surface was then proposed to describe the surface structure of HAP. The interior layer retains the atomic configurations in crystal. The middle layer has its atoms moved and its groups rotated about their original locations. In the surface layer, the atomic arrangements are totally different from those in crystal. In particular for the hydroxyl groups, they move outward and cover the Ca(2+) ions, leaving holes occupied by the phosphate groups. Our study suggested a new model with disordered surface structures for studying the interaction of HAP-based biomaterials with other molecules. PMID:27096760
List-Based Simulated Annealing Algorithm for Traveling Salesman Problem.
Zhan, Shi-hua; Lin, Juan; Zhang, Ze-jun; Zhong, Yi-wen
2016-01-01
Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to solve traveling salesman problem (TSP). LBSA algorithm uses a novel list-based cooling schedule to control the decrease of temperature. Specifically, a list of temperatures is created first, and then the maximum temperature in list is used by Metropolis acceptance criterion to decide whether to accept a candidate solution. The temperature list is adapted iteratively according to the topology of the solution space of the problem. The effectiveness and the parameter sensitivity of the list-based cooling schedule are illustrated through benchmark TSP problems. The LBSA algorithm, whose performance is robust on a wide range of parameter values, shows competitive performance compared with some other state-of-the-art algorithms. PMID:27034650
A laboratory flash furnace for strand annealing simulation
Page, J. H. R.
1995-08-01
The economic production of CRML steels depends on the use of continuous annealing. Successful development of improved CRML steels, the compositions of which have moved to lower carbon contents, is critically dependent on the rate of heating and its effect on transformation characteristics. As a result, accurate simulation of annealing conditions, particularly the heating rate, is essential. With this in mind, European Electrical Steels set criteria for a laboratory annealing facility that would, das far as was practicable, reproduce day- to- day continuous furnace operation. This paper outlines the design criteria, construction, and operation of the resulting annealing facility.
A laboratory flash furnace for strand annealing simulation
Page, J.H.R. [European Electrical Steels, Newport (United Kingdom). Orb Works
1995-08-01
The economic production of CRML steels depends on the use of continuous annealing. Successful developed of improved CRML steels, the compositions of which have moved to lower carbon contents, is critically dependent on the rate of heating and its effect on transformation characteristics. As a result, accurate simulation of annealing conditions, particularly the heating rate, is essential. With this in mind, European Electrical Steels set criteria for a laboratory annealing facility that would, as far as was practicable, reproduce day-to-day continuous furnace operation. This paper outlines the design criteria, construction, and operation of the resulting annealing facility.
A NEW GENETIC SIMULATED ANNEALING ALGORITHM FOR FLOOD ROUTING MODEL
KANG Ling; WANG Cheng; JIANG Tie-bing
2004-01-01
In this paper, a new approach, the Genetic Simulated Annealing (GSA), was proposed for optimizing the parameters in the Muskingum routing model. By integrating the simulated annealing method into the genetic algorithm, the hybrid method could avoid some troubles of traditional methods, such as arduous trial-and-error procedure, premature convergence in genetic algorithm and search blindness in simulated annealing. The principle and implementing procedure of this algorithm were described. Numerical experiments show that the GSA can adjust the optimization population, prevent premature convergence and seek the global optimal result.Applications to the Nanyunhe River and Qingjiang River show that the proposed approach is of higher forecast accuracy and practicability.
Stochastic search in structural optimization - Genetic algorithms and simulated annealing
Hajela, Prabhat
1993-01-01
An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.
An improved simulated annealing algorithm for standard cell placement
Jones, Mark; Banerjee, Prithviraj
1988-01-01
Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the problem of placing standard logic cells in a VLSI ship so that the total interconnection wire length is minimized. An improved standard cell placement algorithm that takes advantage of the performance enhancements that appear to come from parallelizing the uniprocessor simulated annealing algorithm is presented. An outline of this algorithm is given.
Nonsmooth trajectory optimization - An approach using continuous simulated annealing
Lu, Ping; Khan, M. A.
1993-01-01
An account is given of the properties of a continuous simulated annealing algorithm that can function as a global optimization tool for nonsmooth dynamic systems, as shown in the case of a trajectory-optimization program implementation. The approach is shown to successfully solve the problem of nonsmooth trajectory optimization for a high performance rigid-body aircraft. The results obtained demonstrate the superiority of the simulated annealing algorithm over widely used algorithms.
Model based matching using simulated annealing and a minimum representation size criterion
Ravichandran, B.; Sanderson, A. C.
1992-01-01
We define the model based matching problem in terms of the correspondence and transformation that relate the model and scene, and the search and evaluation measures needed to find the best correspondence and transformation. Simulated annealing is proposed as a method for search and optimization, and the minimum representation size criterion is used as the evaluation measure in an algorithm that finds the best correspondence. An algorithm based on simulated annealing is presented and evaluated. This algorithm is viewed as a part of an adaptive, hierarchical approach which provides robust results for a variety of model based matching problems.
Simulated quantum annealing of double-well and multiwell potentials.
Inack, E M; Pilati, S
2015-11-01
We analyze the performance of quantum annealing as a heuristic optimization method to find the absolute minimum of various continuous models, including landscapes with only two wells and also models with many competing minima and with disorder. The simulations performed using a projective quantum Monte Carlo (QMC) algorithm are compared with those based on the finite-temperature path-integral QMC technique and with classical annealing. We show that the projective QMC algorithm is more efficient than the finite-temperature QMC technique, and that both are inferior to classical annealing if this is performed with appropriate long-range moves. However, as the difficulty of the optimization problem increases, classical annealing loses efficiency, while the projective QMC algorithm keeps stable performance and is finally the most effective optimization tool. We discuss the implications of our results for the outstanding problem of testing the efficiency of adiabatic quantum computers using stochastic simulations performed on classical computers. PMID:26651813
Monte Carlo simulation of primary recrystallization and annealing twinning
The formation of annealing twins has been studied from the beginning of the 20th century and a variety of mechanisms have been suggested. Molecular dynamics simulations on the atomic scale have also been performed. This paper reports a microscale simulation of primary recrystallization and twinning of a nickel alloy based on the Monte Carlo approach. Different twin morphologies were simulated. A possible dependence of grain growth direction on twin formation during annealing was demonstrated. The formation of incoherent Σ3 and Σ9 boundaries is verified as the indirect outcome after coherent Σ3 formation
Quantum versus simulated annealing in wireless interference network optimization
Wang, Chi; Chen, Huo; Jonckheere, Edmond
2016-01-01
Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed. PMID:27181056
Quantum versus simulated annealing in wireless interference network optimization
Wang, Chi; Chen, Huo; Jonckheere, Edmond
2016-05-01
Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.
On simulated annealing phase transitions in phylogeny reconstruction.
Strobl, Maximilian A R; Barker, Daniel
2016-08-01
Phylogeny reconstruction with global criteria is NP-complete or NP-hard, hence in general requires a heuristic search. We investigate the powerful, physically inspired, general-purpose heuristic simulated annealing, applied to phylogeny reconstruction. Simulated annealing mimics the physical process of annealing, where a liquid is gently cooled to form a crystal. During the search, periods of elevated specific heat occur, analogous to physical phase transitions. These simulated annealing phase transitions play a crucial role in the outcome of the search. Nevertheless, they have received comparably little attention, for phylogeny or other optimisation problems. We analyse simulated annealing phase transitions during searches for the optimal phylogenetic tree for 34 real-world multiple alignments. In the same way in which melting temperatures differ between materials, we observe distinct specific heat profiles for each input file. We propose this reflects differences in the search landscape and can serve as a measure for problem difficulty and for suitability of the algorithm's parameters. We discuss application in algorithmic optimisation and as a diagnostic to assess parameterisation before computationally costly, large phylogeny reconstructions are launched. Whilst the focus here lies on phylogeny reconstruction under maximum parsimony, it is plausible that our results are more widely applicable to optimisation procedures in science and industry. PMID:27150349
Simulated annealing optimization for multi-objective economic dispatch solution
Ismail ZIANE
2014-11-01
Full Text Available This paper presents a multi-objective Simulated Annealing Optimization to solve a Dynamic Generation Dispatch problem. In this work, the problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are the generating unit capacity limits while the equality constraint is generation-demand balance. To show the advantages of the proposed algorithm, it has been applied for solving multi-objective EELD problems in a 3-generator system with NOx and SO2 emission. Results obtained with Simulated Annealing have been compared with other existing relevant approaches available in literatures. Experimental results show a proficiency of Simulated Annealing over other existing techniques in terms of robustness.
SIMULATED ANNEALING BASED POLYNOMIAL TIME QOS ROUTING ALGORITHM FOR MANETS
Liu Lianggui; Feng Guangzeng
2006-01-01
Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The paper outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.
The Simulated Annealing Algorithm Implemented by the MATLAB
Lin Lin
2012-11-01
Full Text Available This paper expounds the basic principle of simulated annealing algorithm which was applied to solve the function optimization problem and the algorithm realization process by using MATLAB language. Through the improvement algorithm results show that the method is able to function for global optimization, effectively overcome the based on the derivative of the optimization algorithm easy to fall into local optimum problems. This method not only can deepen the understanding of the simulated annealing process, but also can achieve the purpose of design intelligent system.
Coordination Hydrothermal Interconnection Java-Bali Using Simulated Annealing
Wicaksono, B.; Abdullah, A. G.; Saputra, W. S.
2016-04-01
Hydrothermal power plant coordination aims to minimize the total cost of operating system that is represented by fuel costand constraints during optimization. To perform the optimization, there are several methods that can be used. Simulated Annealing (SA) is a method that can be used to solve the optimization problems. This method was inspired by annealing or cooling process in the manufacture of materials composed of crystals. The basic principle of hydrothermal power plant coordination includes the use of hydro power plants to support basic load while thermal power plants were used to support the remaining load. This study used two hydro power plant units and six thermal power plant units with 25 buses by calculating transmission losses and considering power limits in each power plant unit aided by MATLAB software during the process. Hydrothermal power plant coordination using simulated annealing plants showed that a total cost of generation for 24 hours is 13,288,508.01.
The afforestation problem: a heuristic method based on simulated annealing
Vidal, Rene Victor Valqui
1992-01-01
This paper presents the afforestation problem, that is the location and design of new forest compartments to be planted in a given area. This optimization problem is solved by a two-step heuristic method based on simulated annealing. Tests and experiences with this method are also presented....
Analysis of Trivium by a Simulated Annealing variant
Borghoff, Julia; Knudsen, Lars Ramkilde; Matusiewicz, Krystian
2010-01-01
characteristic of equation systems that may be efficiently solvable by the means of such algorithms is provided. As an example, we investigate equation systems induced by the problem of recovering the internal state of the stream cipher Trivium. We propose an improved variant of the simulated annealing method...
Function minimization with partially correct data via simulated annealing
Lorre, Jean J.
1988-01-01
The simulated annealing technique has been applied successfully to the problem of estimating the coefficients of a function in cases where only a portion of the data being fitted to the function is truly representative of the function, the rest being erroneous. Two examples are given, one in photometric function fitting and the other in pattern recognition. A schematic of the algorithm is provided.
Physical Mapping Using Simulated Annealing and Evolutionary Algorithms
Vesterstrøm, Jacob Svaneborg
2003-01-01
Physical mapping (PM) is a method of bioinformatics that assists in DNA sequencing. The goal is to determine the order of a collection of fragments taken from a DNA strand, given knowledge of certain unique DNA markers contained in the fragments. Simulated annealing (SA) is the most widely used...
A Simulated Annealing Methodology for Clusterwise Linear Regression.
DeSarbo, Wayne S.; And Others
1989-01-01
A method is presented that simultaneously estimates cluster membership and corresponding regression functions for a sample of observations or subjects. This methodology is presented with the simulated annealing-based algorithm. A set of Monte Carlo analyses is included to demonstrate the performance of the algorithm. (SLD)
Application of Simulated Annealing to Clustering Tuples in Databases.
Bell, D. A.; And Others
1990-01-01
Investigates the value of applying principles derived from simulated annealing to clustering tuples in database design, and compares this technique with a graph-collapsing clustering method. It is concluded that, while the new method does give superior results, the expense involved in algorithm run time is prohibitive. (24 references) (CLB)
Meta-Modeling by Symbolic Regression and Pareto Simulated Annealing
Stinstra, E.; Rennen, G.; Teeuwen, G.J.A.
2006-01-01
The subject of this paper is a new approach to Symbolic Regression.Other publications on Symbolic Regression use Genetic Programming.This paper describes an alternative method based on Pareto Simulated Annealing.Our method is based on linear regression for the estimation of constants.Interval arithm
Thermal, quantum and simulated quantum annealing: analytical comparisons for simple models
Bapst, Victor; Semerjian, Guilhem
2015-01-01
We study various annealing dynamics, both classical and quantum, for simple mean-field models and explain how to describe their behavior in the thermodynamic limit in terms of differential equations. In particular we emphasize the differences between quantum annealing (i.e. evolution with Schr\\"odinger equation) and simulated quantum annealing (i.e. annealing of a Quantum Monte Carlo simulation).
Particle Based Image Segmentation with Simulated Annealing
Everts, M.H.; Bekker, H.; Jalba, A.C.; Roerdink, J.B.T.M.
2007-01-01
The Charged Particle Model (CPM) is a physically motivated deformable model for shape recovery and segmentation. It simulates a system of charged particles moving in an electric field generated from the input image, whose positions in the equilibrium state are used for curve or surface reconstructio
The Simulated Annealing Algorithm Implemented by the MATLAB
Lin Lin; Chen Fei
2012-01-01
This paper expounds the basic principle of simulated annealing algorithm which was applied to solve the function optimization problem and the algorithm realization process by using MATLAB language. Through the improvement algorithm results show that the method is able to function for global optimization, effectively overcome the based on the derivative of the optimization algorithm easy to fall into local optimum problems. This method not only can deepen the understanding of the simulated ann...
Molecular dynamics simulation of annealed ZnO surfaces
Min, Tjun Kit; Yoon, Tiem Leong [School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia); Lim, Thong Leng [Faculty of Engineering and Technology, Multimedia University, Melaka Campus, 75450 Melaka (Malaysia)
2015-04-24
The effect of thermally annealing a slab of wurtzite ZnO, terminated by two surfaces, (0001) (which is oxygen-terminated) and (0001{sup ¯}) (which is Zn-terminated), is investigated via molecular dynamics simulation by using reactive force field (ReaxFF). We found that upon heating beyond a threshold temperature of ∼700 K, surface oxygen atoms begin to sublimate from the (0001) surface. The ratio of oxygen leaving the surface at a given temperature increases as the heating temperature increases. A range of phenomena occurring at the atomic level on the (0001) surface has also been explored, such as formation of oxygen dimers on the surface and evolution of partial charge distribution in the slab during the annealing process. It was found that the partial charge distribution as a function of the depth from the surface undergoes a qualitative change when the annealing temperature is above the threshold temperature.
Molecular dynamics simulation of annealed ZnO surfaces
The effect of thermally annealing a slab of wurtzite ZnO, terminated by two surfaces, (0001) (which is oxygen-terminated) and (0001¯) (which is Zn-terminated), is investigated via molecular dynamics simulation by using reactive force field (ReaxFF). We found that upon heating beyond a threshold temperature of ∼700 K, surface oxygen atoms begin to sublimate from the (0001) surface. The ratio of oxygen leaving the surface at a given temperature increases as the heating temperature increases. A range of phenomena occurring at the atomic level on the (0001) surface has also been explored, such as formation of oxygen dimers on the surface and evolution of partial charge distribution in the slab during the annealing process. It was found that the partial charge distribution as a function of the depth from the surface undergoes a qualitative change when the annealing temperature is above the threshold temperature
Application of simulated annealing algorithm to optimizing sequencing of operation steps
无
2000-01-01
Discusses the optimization of machining operation sequencing by simulated annealing, and building a simulated annealing optimization model. From which, a new way to optimize operation sequencing can be developed.
Optimization of pipe networks including pumps by simulated annealing
Costa A.L.H.; Medeiros J.L.; Pessoa F.L.P.
2000-01-01
The objective of this work is to present an application of the simulated annealing method for the optimal design of pipe networks including pumps. Although its importance, the optimization of pumped networks did not receive great attention in the literature. The proposed search scheme explores the discrete space of the decision variables: pipe diameters and pump sizes. The behavior of the pumps is describe through the characteristic curve, generating more realistic solutions. In order to demo...
Convergence of simulated annealing by the generalized transition probability
Nishimori, Hidetoshi; Inoue, Jun-Ichi
1998-01-01
We prove weak ergodicity of the inhomogeneous Markov process generated by the generalized transition probability of Tsallis and Stariolo under power-law decay of the temperature. We thus have a mathematical foundation to conjecture convergence of simulated annealing processes with the generalized transition probability to the minimum of the cost function. An explicitly solvable example in one dimension is analyzed in which the generalized transition probability leads to a fast convergence of ...
Optimization of multiple-layer microperforated panels by simulated annealing
Ruiz Villamil, Heidi; Cobo, Pedro; Jacobsen, Finn
2011-01-01
Sound absorption by microperforated panels (MPP) has received increasing attention the past years as an alternative to conventional porous absorbers in applications with special cleanliness and health requirements. The absorption curve of an MPP depends on four parameters: the holes diameter, the....... Therefore, simulated annealing is proposed in this paper as a tool to solve the optimization problem of finding the best combination of the constitutive parameters of an ML-MPP providing the maximum average absorption within a prescribed frequency band....
Solving geometric constraints with genetic simulated annealing algorithm
刘生礼; 唐敏; 董金祥
2003-01-01
This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.
Simulated Annealing for the 0/1 Multidimensional Knapsack Problem
Fubin Qian; Rui Ding
2007-01-01
In this paper a simulated annealing (SA) algorithm is presented for the 0/1 multidimensional knapsack problem. Problem-specific knowledge is incorporated in the algorithm description and evaluation of parameters in order to look into the performance of finite-time implementations of SA. Computational results show that SA performs much better than a genetic algorithm in terms of solution time, whilst having a modest loss of solution quality.
Reversible Jump MCMC Simulated Annealing for Neural Networks
Andrieu, Christophe; De Freitas, Nando; Doucet, Arnaud
2013-01-01
We propose a novel reversible jump Markov chain Monte Carlo (MCMC) simulated annealing algorithm to optimize radial basis function (RBF) networks. This algorithm enables us to maximize the joint posterior distribution of the network parameters and the number of basis functions. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. We also show that by calibrating a Bayesian model, we can obtain the classical...
Simulated annealing spectral clustering algorithm for image segmentation
Yifang Yang; and Yuping Wang
2014-01-01
The similarity measure is crucial to the performance of spectral clustering. The Gaussian kernel function based on the Euclidean distance is usual y adopted as the similarity mea-sure. However, the Euclidean distance measure cannot ful y reveal the complex distribution data, and the result of spectral clustering is very sensitive to the scaling parameter. To solve these problems, a new manifold distance measure and a novel simulated anneal-ing spectral clustering (SASC) algorithm based on the manifold distance measure are proposed. The simulated annealing based on genetic algorithm (SAGA), characterized by its rapid conver-gence to the global optimum, is used to cluster the sample points in the spectral mapping space. The proposed algorithm can not only reflect local and global consistency better, but also reduce the sensitivity of spectral clustering to the kernel parameter, which improves the algorithm’s clustering performance. To efficiently ap-ply the algorithm to image segmentation, the Nystr¨om method is used to reduce the computation complexity. Experimental re-sults show that compared with traditional clustering algorithms and those popular spectral clustering algorithms, the proposed algorithm can achieve better clustering performances on several synthetic datasets, texture images and real images.
Adaptive Sampling in Hierarchical Simulation
Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R
2007-07-09
We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.
Reticle Floorplanning and Simulated Wafer Dicing for Multiple-Project Wafers by Simulated Annealing
Lin, Rung-Bin; Wu, Meng-Chiou; Tsai, Shih-Cheng
2008-01-01
In this chapter we have demonstrated how simulated annealing is used to solve two NPhard problems: simulated wafer dicing and reticle floorplanning problems for MPW. For simulated wafer dicing, we suggest that HVMIS-SA-Z be employed to find the wafer dicing plans, especially for low-volume production. As for reticle floorplanning, BT-VOCO and
Optimisation of electron beam characteristics by simulated annealing
Full text: With the development of technology in the field of treatment beam delivery, the possibility of tailoring radiation beams (via manipulation of the beam's phase space) is foreseeable. This investigation involved evaluating a method for determining the characteristics of pure electron beams which provided dose distributions that best approximated desired distributions. The aim is to determine which degrees of freedom are advantageous and worth pursuing in a clinical setting. A simulated annealing routine was developed to determine optimum electron beam characteristics. A set of beam elements are defined at the surface of a homogeneous water equivalent phantom defining discrete positions and angles of incidence, and electron energies. The optimal weighting of these elements is determined by the (generally approximate) solution to the linear equation, Dw = d, where d represents the dose distribution calculated over the phantom, w the vector of (50 - 2x104) beam element relative weights, and D a normalised matrix of dose deposition kernels. In the iterative annealing procedure, beam elements are randomly selected and beam weighting distributions are sampled and used to perturb the selected elements. Perturbations are accepted or rejected according to standard simulated annealing criteria. The result (after the algorithm has terminated due to meeting an iteration or optimisation specification) is an approximate solution for the beam weight vector (w) specified by the above equation. This technique has been applied for several sample dose distributions and phase space restrictions. An example is given of the phase space obtained when endeavouring to conform to a rectangular 100% dose region with polyenergetic though normally incident electrons. For regular distributions, intuitive conclusions regarding the benefits of energy/angular manipulation may be made, whereas for complex distributions, variations in intensity over beam elements of varying energy and
Morgan, John A
2016-01-01
The method of simulated annealing is adapted to the temperature-emissivity separation (TES) problem. A patch of surface at the bottom of the atmosphere is assumed to be a greybody emitter with spectral emissivity $\\epsilon(k)$ describable by a mixture of spectral endmembers. We prove that a simulated annealing search conducted according to a suitable schedule converges to a solution maximizing the $\\textit{A-Posteriori}$ probability that spectral radiance detected at the top of the atmosphere originates from a patch with stipulated $T$ and $\\epsilon(k)$. Any such solution will be nonunique. The average of a large number of simulated annealing solutions, however, converges almost surely to a unique Maximum A-Posteriori solution for $T$ and $\\epsilon(k)$. The limitation to a stipulated set of endmember emissivities may be relaxed by allowing the number of endmembers to grow without bound, and to be generic continuous functions of wavenumber with bounded first derivatives with respect to wavenumber.
Job Shop Scheduling Using Modified Simulated Annealing Algorithm
PV Senthiil
2014-09-01
Full Text Available Timely and cost factor is increasingly important in today’s global competitive market. The key problem faced by today’s industries are feasible allocation of various jobs to available resources i.e., machines (Scheduling and optimal utilization of the available resources. Among the various problems in scheduling, the job shop scheduling is the most complicated and requires a large computational effort to solve it. A typical job shop scheduling problem has a set of jobs to be processed in a set of machines, with certain constraints and objective function to be achieved. The most commonly considered objectives are the minimization of make span, minimization of tardiness which leads to minimization of penalty cost, and to maximize machine utilization. Machine shop scheduling can be done using various techniques like standard dispatching rules, heuristic techniques like Simulated annealing, Tabu Search, Genetic algorithm, etc,.here a typical job shop shop scheduling problem is solved using simulated annealing(SA technique, a heuristic search algorithm. SA is generic neighbourhood search algorithm used to locate optimal solution very nearer to global optimal solution. A software based program is developed in VB platform for a typical job shop problem and test instances were performed over it. Experimental results obtained were further tuned by varying parameters and optimal results were obtained
Simulated annealing technique to design minimum cost exchanger
Khalfe Nadeem M.
2011-01-01
Full Text Available Owing to the wide utilization of heat exchangers in industrial processes, their cost minimization is an important target for both designers and users. Traditional design approaches are based on iterative procedures which gradually change the design and geometric parameters to satisfy a given heat duty and constraints. Although well proven, this kind of approach is time consuming and may not lead to cost effective design as no cost criteria are explicitly accounted for. The present study explores the use of nontraditional optimization technique: called simulated annealing (SA, for design optimization of shell and tube heat exchangers from economic point of view. The optimization procedure involves the selection of the major geometric parameters such as tube diameters, tube length, baffle spacing, number of tube passes, tube layout, type of head, baffle cut etc and minimization of total annual cost is considered as design target. The presented simulated annealing technique is simple in concept, few in parameters and easy for implementations. Furthermore, the SA algorithm explores the good quality solutions quickly, giving the designer more degrees of freedom in the final choice with respect to traditional methods. The methodology takes into account the geometric and operational constraints typically recommended by design codes. Three different case studies are presented to demonstrate the effectiveness and accuracy of proposed algorithm. The SA approach is able to reduce the total cost of heat exchanger as compare to cost obtained by previously reported GA approach.
Simulated Annealing-Based Krill Herd Algorithm for Global Optimization
Gai-Ge Wang
2013-01-01
Full Text Available Recently, Gandomi and Alavi proposed a novel swarm intelligent method, called krill herd (KH, for global optimization. To enhance the performance of the KH method, in this paper, a new improved meta-heuristic simulated annealing-based krill herd (SKH method is proposed for optimization tasks. A new krill selecting (KS operator is used to refine krill behavior when updating krill’s position so as to enhance its reliability and robustness dealing with optimization problems. The introduced KS operator involves greedy strategy and accepting few not-so-good solutions with a low probability originally used in simulated annealing (SA. In addition, a kind of elitism scheme is used to save the best individuals in the population in the process of the krill updating. The merits of these improvements are verified by fourteen standard benchmarking functions and experimental results show that, in most cases, the performance of this improved meta-heuristic SKH method is superior to, or at least highly competitive with, the standard KH and other optimization methods.
Time series forecasting using a TSK fuzzy system tuned with simulated annealing
Almaraashi, Majid; John, Robert; Coupland, Simon; Hopgood, Adrian
2010-01-01
In this paper, a combination of a Takagi-Sugeno fuzzy system (TSK) and simulated annealing is used to predict well known time series by searching for the best configuration of the fuzzy system. Simulated annealing is used to optimise the parameters of the antecedent and the consequent parts of the fuzzy system rules. The results of the proposed method are encouraging indicating that simulated annealing and fuzzy logic are able to combine well in time series prediction.
Memoryless cooperative graph search based on the simulated annealing algorithm
Hou Jian; Yan Gang-Feng; Fan Zhen
2011-01-01
We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip consensus method based scheme is presented to update the key parameter-radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.
Optimal placement of excitations and sensors by simulated annealing
Salama, Moktar; Bruno, R.; Chen, G.-S.; Garba, J.
1989-01-01
The optimal placement of discrete actuators and sensors is posed as a combinatorial optimization problem. Two examples for truss structures were used for illustration; the first dealt with the optimal placement of passive dampers along existing truss members, and the second dealt with the optimal placement of a combination of a set of actuators and a set of sensors. Except for the simplest problems, an exact solution by enumeration involves a very large number of function evaluations, and is therefore computationally intractable. By contrast, the simulated annealing heuristic involves far fewer evaluations and is best suited for the class of problems considered. As an optimization tool, the effectiveness of the algorithm is enhanced by introducing a number of rules that incorporate knowledge about the physical behavior of the problem. Some of the suggested rules are necessarily problem dependent.
Simulated annealing and joint manufacturing batch-sizing
Sarker Ruhul
2003-01-01
Full Text Available We address an important problem of a manufacturing system. The system procures raw materials from outside suppliers in a lot and processes them to produce finished goods. It proposes an ordering policy for raw materials to meet the requirements of a production facility. In return, this facility has to deliver finished products demanded by external buyers at fixed time intervals. First, a general cost model is developed considering both raw materials and finished products. Then this model is used to develop a simulated annealing approach to determining an optimal ordering policy for procurement of raw materials and also for the manufacturing batch size to minimize the total cost for meeting customer demands in time. The solutions obtained were compared with those of traditional approaches. Numerical examples are presented. .
Simulated Annealing Algorithm and Its Application in Irregular Polygons Packing
段国林; 王彩红; 张健楠
2003-01-01
Two-dimensional irregular polygons packing problem is very difficult to be solved in traditional optimal way.Simulated annealing(SA)algorithm is a stochastic optimization technique that can be used to solve packing problems.The whole process of SA is introduced firstly in this paper. An extended neighborhood searching method in SA is mainly analyzed. A general module of SA algorithm is given and used to lay out the irregular polygons. The judgment of intersection and other constrains of irregular polygons are analyzed. Then an example that was used in the paper of Stefan Jakobs is listed.Results show that this SA algorithm shortens the computation time and improves the solution.
Solving the dynamic berth allocation problem by simulated annealing
Lin, Shih-Wei; Ting, Ching-Jung
2014-03-01
Berth allocation, the first operation when vessels arrive at a port, is one of the major container port optimization problems. From both the port operator's and the ocean carriers' perspective, minimization of the time a ship spends at berth is a key goal of port operations. This article focuses on two versions of the dynamic berth allocation problem (DBAP): discrete and continuous cases. The first case assigns ships to a given set of berth positions; the second one permits them to be moored anywhere along the berth. Simulated annealing (SA) approaches are proposed to solve the DBAP. The proposed SAs are tested with numerical instances for different sizes from the literature. Experimental results show that the proposed SA can obtain the optimal solutions in all instances of discrete cases and update 27 best known solutions in the continuous case.
Restoration of polarimetric SAR images using simulated annealing
Schou, Jesper; Skriver, Henning
2001-01-01
Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...... approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented...... applicable to multilook polarimetric SAR images, resulting in an estimate of the mean covariance matrix rather than the RCS. Small windows are applied in the filtering, and due to the iterative nature of the approach, reasonable estimates of the polarimetric quantities characterizing the distributed targets...
Simulated Annealing Clustering for Optimum GPS Satellite Selection
M. Ranjbar
2012-05-01
Full Text Available This paper utilizes a clustering approach based on Simulated Annealing (SA method to select optimum satellite subsets from the visible satellites. Geometric Dilution of Precision (GDOP is used as criteria of optimality. The lower the values of the GDOP number, the better the geometric strength, and vice versa. Not needing to calculate the inverse matrix, which is time-consuming process, is a dramatically important advantage of using this method, so a great reduction in computational cost is achieved. SA is a powerful technique to obtain a close approximation to the global optimum for a given problem. The evaluation of the performance of the proposed method is done by validation measures. The external validation measures, entropy and purity, are used to measure the extent to which cluster labels affirm with the externally given class labels. The overall purity and entropy is 0.9015 and 0.3993, respectively which is an excellent result.
Graeme J. Doole
2007-01-01
This short paper provides a simple introduction on how a simulation model implemented in Microsoft Excel® can be optimised using Visual Basic for Applications (VBA) programming and the compressed simulated annealing algorithm (Ohlmann et al., 2004; Ohlmann and Thomas, 2007). The standard simulated annealing procedure enters as a special case. Practical advice for determining the parameters that guide the stochastic search process in an annealing algorithm is also given.
Simulation of dopant diffusion and activation during flash lamp annealing
Zechner, Christoph [Synopsys Switzerland LLC, Affolternstrasse 52, CH-8050 Zurich (Switzerland); Matveev, Dmitri [Synopsys Switzerland LLC, Affolternstrasse 52, CH-8050 Zurich (Switzerland)], E-mail: matveev@synopsys.com; Zographos, Nikolas [Synopsys Switzerland LLC, Affolternstrasse 52, CH-8050 Zurich (Switzerland); Lerch, Wilfried; Paul, Silke [Mattson Thermal Products GmbH, Daimlerstrasse 10, D-89160 Dornstadt (Germany)
2008-12-05
A set of advanced models implemented into the simulator Sentaurus Process was applied to simulate ultra shallow junction formation by flash lamp annealing (FLA). The full path transient enhanced diffusion model includes equations for small interstitial clusters (I{sub 2}, I{sub 3}, I{sub 4}), {l_brace}3 1 1{r_brace} defects and dislocation loops. A dopant-point defect clustering model is used for dopant activation simulation. Several cluster types are considered: B{sub 2}, B{sub 2}I, B{sub 2}I{sub 2}, B{sub 3}I, B{sub 3}I{sub 2}, B{sub 3}I{sub 3} for boron and As{sub 2}, As{sub 2}V, As{sub 3}, As{sub 3}V, As{sub 4}, As{sub 4}V for arsenic. Different point defect and dopant-point defect pair charge states are taken into account to obtain accurate results in the high doping level region. The flux expressions in the three-phase segregation model include a dependence on the doping level and point defect supersaturation. The FLA process was performed at various peak temperatures in a Mattson Millios{sup TM} fRTP{sup TM} system. The measured wafer temperature as a function of time allowed us to simulate the transient processes with a high accuracy. A good agreement between secondary ion mass spectroscopy (SIMS) and simulated profiles was achieved. The sheet resistance dependence on the FLA peak temperature was reproduced successfully.
A Knowledge-Based Simulated Annealing Algorithm to Multiple Satellites Mission Planning Problems
Da-Wei Jin; Li-Ning Xing
2013-01-01
The multiple satellites mission planning is a complex combination optimization problem. A knowledge-based simulated annealing algorithm is proposed to the multiple satellites mission planning problems. The experimental results suggest that the proposed algorithm is effective to the given problem. The knowledge-based simulated annealing method will provide a useful reference for the improvement of existing optimization approaches.
UN ALGORITMO DI SIMULATED ANNEALING PER LA SOLUZIONE DI UN PROBLEMA DI SCHEDULING
Crescenzio Gallo
2004-01-01
An algorithm of "Simulated Annealing" for solving scheduling problems is presented. The issues related to scheduling are discussed, together with the Simulated Annealing approximation method and its main parameters (freezing, temperature, cooling, number of neighbourhoods to explore), the choices made in defining them for the generation of a good algorithm that efficiently resolves the scheduling problem.
Pelletier, Mariane
1998-01-01
We study convergence rates of $\\mathbb{R}$-valued algorithms, especially in the case of multiple targets and simulated annealing. We precise, for example, the convergence rate of simulated annealing algorithms, whose weak convergence to a distribution concentrated on the potential's minima had been established by Gelfand and Mitter or by Hwang and Sheu.
稻垣, 陽介; イナガキ, ヨウスケ; Yousuke, Inagaki
2007-01-01
The efficiency of Monte Carlo simulated annealing algorithm based on the generalized statistics of Tsallis (GSA) is compared with conventional simulated annealing (CSA) based on Boltzmann-Gibbs statistics. Application to the discrete-time optimal growth problem demonstrates that the replacement of CSA by GSA has the potential to speed up optimizations with no loss of accuracy in finding optimal policy function.
A Simulated Annealing Algorithm for Training Empirical Potential Functions of Protein Folding
WANG Yu-hong; LI Wei
2005-01-01
In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a solution of the problem based upon the simulated annealing algorithm. This simulated annealing algorithm is indispensable for developing and testing highly refined empirical potential functions.
Time Simulation of Bone Adaptation
Bagge, Mette
1998-01-01
The structural adaptation of a three-dimensional finite element model ofthe proximal femur is considered. Presuming the bone possesses the optimalstructure under the given loads, the bone material distribution is foundby minimizing the strain energy averaged over ten load cases with avolume...... constraint. Theoptimized design is used as a start-configuration for the remodelingsimulation.The parameter characterizing the equilibrium level where no remodeling occurs is estimated from the optimization parameters.The loads vary in magnitude, location and direction simulating timedependent loading. The...
Application of Simulated Annealing and Related Algorithms to TWTA Design
Radke, Eric M.
2004-01-01
Simulated Annealing (SA) is a stochastic optimization algorithm used to search for global minima in complex design surfaces where exhaustive searches are not computationally feasible. The algorithm is derived by simulating the annealing process, whereby a solid is heated to a liquid state and then cooled slowly to reach thermodynamic equilibrium at each temperature. The idea is that atoms in the solid continually bond and re-bond at various quantum energy levels, and with sufficient cooling time they will rearrange at the minimum energy state to form a perfect crystal. The distribution of energy levels is given by the Boltzmann distribution: as temperature drops, the probability of the presence of high-energy bonds decreases. In searching for an optimal design, local minima and discontinuities are often present in a design surface. SA presents a distinct advantage over other optimization algorithms in its ability to escape from these local minima. Just as high-energy atomic configurations are visited in the actual annealing process in order to eventually reach the minimum energy state, in SA highly non-optimal configurations are visited in order to find otherwise inaccessible global minima. The SA algorithm produces a Markov chain of points in the design space at each temperature, with a monotonically decreasing temperature. A random point is started upon, and the objective function is evaluated at that point. A stochastic perturbation is then made to the parameters of the point to arrive at a proposed new point in the design space, at which the objection function is evaluated as well. If the change in objective function values (Delta)E is negative, the proposed new point is accepted. If (Delta)E is positive, the proposed new point is accepted according to the Metropolis criterion: rho((Delta)f) = exp((-Delta)E/T), where T is the temperature for the current Markov chain. The process then repeats for the remainder of the Markov chain, after which the temperature is
Optimization of Electric Power Distribution Using Hybrid Simulated Annealing Approach
Walid Ahmed
2008-01-01
Full Text Available The key goal of electric power distribution companies is to provide a high quality of service with a low cost of operation. The growing customer needs requires a re-distribution of the Power over various nodes of the Distributed Generation (DG facilitates. The re-distribution might cause over load on various parts of the networks which if not correctly optimized might increase the cost of maintenance and affect the overall network reliability. This is why it is urgently requited to find a methodology that can effectively provide a schema for re-distribution of the power and achieve both customers and power companies contracting objectives. In this paper, we explore our new proposed idea of using a simulated annealing based local search technique to provide an efficient power load distribution for distributed generation network. On doing this, we will apply our approach on the famous IEEE14 and IEEE30 power systems as two test cases. The developed results show the significant of the proposed approach.
Evolutionary algorithms, simulated annealing, and Tabu search: a comparative study
Youssef, Habib; Sait, Sadiq M.; Adiche, Hakim
1998-10-01
Evolutionary algorithms, simulated annealing (SA), and Tabu Search (TS) are general iterative algorithms for combinatorial optimization. The term evolutionary algorithm is used to refer to any probabilistic algorithm whose design is inspired by evolutionary mechanisms found in biological species. Most widely known algorithms of this category are Genetic Algorithms (GA). GA, SA, and TS have been found to be very effective and robust in solving numerous problems from a wide range of application domains.Furthermore, they are even suitable for ill-posed problems where some of the parameters are not known before hand. These properties are lacking in all traditional optimization techniques. In this paper we perform a comparative study among GA, SA, and TS. These algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space. the three heuristics are applied on the same optimization problem and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search from initial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time, and (4) the number of solutions found at successive intervals of the cost function. The benchmark problem was is the floorplanning of very large scale integrated circuits. This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation function, which is then used to rate competing solutions.
Simulated Annealing Technique for Routing in a Rectangular Mesh Network
Noraziah Adzhar
2014-01-01
Full Text Available In the process of automatic design for printed circuit boards (PCBs, the phase following cell placement is routing. On the other hand, routing process is a notoriously difficult problem, and even the simplest routing problem which consists of a set of two-pin nets is known to be NP-complete. In this research, our routing region is first tessellated into a uniform Nx×Ny array of square cells. The ultimate goal for a routing problem is to achieve complete automatic routing with minimal need for any manual intervention. Therefore, shortest path for all connections needs to be established. While classical Dijkstra’s algorithm guarantees to find shortest path for a single net, each routed net will form obstacles for later paths. This will add complexities to route later nets and make its routing longer than the optimal path or sometimes impossible to complete. Today’s sequential routing often applies heuristic method to further refine the solution. Through this process, all nets will be rerouted in different order to improve the quality of routing. Because of this, we are motivated to apply simulated annealing, one of the metaheuristic methods to our routing model to produce better candidates of sequence.
Static Security Enhancement and Loss Minimization Using Simulated Annealing
A.Y. Abdelaziz
2013-03-01
Full Text Available This paper presents a developed algorithm for optimal placement of thyristor controlled series capacitors (TCSC’s for enhancing the power system static security and minimizing the system overall power loss. Placing TCSC’s at selected branches requires analysis of the system behavior under all possible contingencies. A selective procedure to determine the locations and settings of the thyristor controlled series capacitors is presented. The locations are determined by evaluating contingency sensitivity index (CSI for a given power system branch for a given number of contingencies. This criterion is then used to develop branches prioritizing index in order to rank the system branches possible for placement of the thyristor controlled series capacitors. Optimal settings of TCSC’s are determined by the optimization technique of simulated annealing (SA, where settings are chosen to minimize the overall power system losses. The goal of the developed methodology is to enhance power system static security by alleviating/eliminating overloads on the transmission lines and maintaining the voltages at all load buses within their specified limits through the optimal placement and setting of TCSC’s under single and double line outage network contingencies. The proposed algorithm is examined using different IEEE standard test systems to shown its superiority in enhancing the system static security and minimizing the system losses.
Traveling Salesman Approach for Solving Petrol Distribution Using Simulated Annealing
Zuhaimy Ismail
2008-01-01
Full Text Available This research presents an attempt to solve a logistic company's problem of delivering petrol to petrol station in the state of Johor. This delivery system is formulated as a travelling salesman problem (TSP. TSP involves finding an optimal route for visiting stations and returning to point of origin, where the inter-station distance is symmetric and known. This real world application is a deceptive simple combinatorial problem and our approach is to develop solutions based on the idea of local search and meta-heuristics. As a standard problem, we have chosen a solution is a deceptively simple combinatorial problem and we defined it simply as the time spends or distance travelled by salesman visiting n cities (or nodes cyclically. In one tour the vehicle visits each station just once and finishes up where he started. As standard problems, we have chosen TSP with different stations visited once. This research presents the development of solution engine based on local search method known as Greedy Method and with the result generated as the initial solution, Simulated Annealing (SA and Tabu Search (TS further used to improve the search and provide the best solution. A user friendly optimization program developed using Microsoft C++ to solve the TSP and provides solutions to future TSP which may be classified into daily or advanced management and engineering problems.
Efficient Hand off using Fuzzy and Simulated Annealing
Vikas.M.N
2012-02-01
Full Text Available This paper presents an efficient method for the hand off mechanism in cellular networks using optimization algorithms. The proposed approach integrates a fuzzy logic approach with simulated annealing algorithm to automate the tuning process. The fuzzy controller carries out inference operation at high-speed, whereas the tuning procedure works at a much lower rate. For the implementation described in this paper, a two-input-one-output fuzzy controller is considered. Both the inputs and the output have 8- bit resolution, and up to seven membership functions for each input or output can be defined over the universe of discourse. The fuzzy controller has two levels of pipeline which allows overlapping of the arithmetic as well as inference operations. The SA tuning mechanism adjusts the triangular or singleton membership functions to minimize a cost function. The complete self-tuned fuzzy inference engine is implemented in a Xilinx SPARTAN3 XC3S200 series FPGA device. This paper describes various aspects of the implementation of the self-tuned hand off system.
I Gede Agus Widyadana
2002-01-01
Full Text Available The research is focused on comparing Genetics algorithm and Simulated Annealing in the term of performa and processing time. The main purpose is to find out performance both of the algorithm to solve minimizing makespan and total flowtime in a particular flowshop system. Performances of the algorithms are found by simulating problems with variation of jobs and machines combination. The result show the Simulated Annealing is much better than the Genetics up to 90%. The Genetics, however, only had score in processing time, but the trend that plotted suggest that in problems with lots of jobs and lots of machines, the Simulated Annealing will run much faster than the Genetics. Abstract in Bahasa Indonesia : Penelitian ini difokuskan pada pembandingan algoritma Genetika dan Simulated Annealing ditinjau dari aspek performa dan waktu proses. Tujuannya adalah untuk melihat kemampuan dua algoritma tersebut untuk menyelesaikan problem-problem penjadwalan flow shop dengan kriteria minimasi makespan dan total flowtime. Kemampuan kedua algoritma tersebut dilihat dengan melakukan simulasi yang dilakukan pada kombinasi-kombinasi job dan mesin yang berbeda-beda. Hasil simulasi menunjukan algoritma Simulated Annealing lebih unggul dari algoritma Genetika hingga 90%, algoritma Genetika hanya unggul pada waktu proses saja, namun dengan tren waktu proses yang terbentuk, diyakini pada problem dengan kombinasi job dan mesin yang banyak, algoritma Simulated Annealing dapat lebih cepat daripada algoritma Genetika. Kata kunci: Algoritma Genetika, Simulated Annealing, flow shop, makespan, total flowtime.
余农; 吴昊; 吴常泳; 李范鸣; 吴立德
2003-01-01
A practical neural network model for morphological filtering and a simulated annealing optimal algorithm for the network parameters training are proposed in this paper. It is pointed out that the optimal designing process of the morphological filtering network in fact is the optimal learning process of adjusting network parameters (structuring element, or SE for short) to accommodate image environment. Then the network structure may possess the characteristics ofimage targets, and so give specific infor- mation to the SE. Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to complex changing image. For application tomotional image target detection, dynamic training algorithm is applied to the designing process using asymptotic shrinking error and appropriate network weights adjusting. Experimental results show that the algorithm has invariant propertywith respect to shift, scale and rotation of moving target in continuing detection of moving targets.
Jonkers, PAE
2001-01-01
A simulation single-electron model is presented to describe the effect of annealing current perpendicular to plane-giant magnetoresistance (CPP-GMR) systems. Progressive annealing is represented by a progressively increasing number of impurities occurring at the interfaces of adjacent layers constit
Sensitivity study on hydraulic well testing inversion using simulated annealing
For environmental remediation, management of nuclear waste disposal, or geothermal reservoir engineering, it is very important to evaluate the permeabilities, spacing, and sizes of the subsurface fractures which control ground water flow. Cluster variable aperture (CVA) simulated annealing has been used as an inversion technique to construct fluid flow models of fractured formations based on transient pressure data from hydraulic tests. A two-dimensional fracture network system is represented as a filled regular lattice of fracture elements. The algorithm iteratively changes an aperture of cluster of fracture elements, which are chosen randomly from a list of discrete apertures, to improve the match to observed pressure transients. The size of the clusters is held constant throughout the iterations. Sensitivity studies using simple fracture models with eight wells show that, in general, it is necessary to conduct interference tests using at least three different wells as pumping well in order to reconstruct the fracture network with a transmissivity contrast of one order of magnitude, particularly when the cluster size is not known a priori. Because hydraulic inversion is inherently non-unique, it is important to utilize additional information. The authors investigated the relationship between the scale of heterogeneity and the optimum cluster size (and its shape) to enhance the reliability and convergence of the inversion. It appears that the cluster size corresponding to about 20--40 % of the practical range of the spatial correlation is optimal. Inversion results of the Raymond test site data are also presented and the practical range of spatial correlation is evaluated to be about 5--10 m from the optimal cluster size in the inversion
A Branch and Bound and Simulated Annealing Approach for Job Shop Scheduling
Tan Hui Woon; Sutinah Salim
2004-01-01
This paper presents two approaches to the solution of the job shop scheduling problem, namely the branch and bound, and simulated annealing approach. The objective is to schedule the jobs on the machines so that the total completion time is minimized. In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which...
Gregorius Satia Budhi
2003-01-01
Full Text Available Flexible Manufacturing System (FMS is a manufacturing system that is formed from several Numerical Controlled Machines combine with material handling system, so that different jobs can be worked by different machines sequences. FMS combine the high productivity and flexibility of Transfer Line and Job Shop manufacturing system. In this reasearch, Activity-Based Costing(ABC approach was used as the weight to search the operation route in the proper machine, so that the total production cost can be optimized. The search method that was used in this experiment is Simulated Annealling, a variant form Hill Climbing Search method. An ideal operation time to proses a part was used as the annealling schedule. From the empirical test, it could be proved that the use of ABC approach and Simulated Annealing to search the route (routing process can optimize the Total Production Cost. In the other hand, the use of ideal operation time to process a part as annealing schedule can control the processing time well. Abstract in Bahasa Indonesia : Flexible Manufacturing System (FMS adalah sistem manufaktur yang tersusun dari mesin-mesin Numerical Control (NC yang dikombinasi dengan Sistem Penanganan Material, sehingga job-job berbeda dikerjakan oleh mesin-mesin dengan alur yang berlainan. FMS menggabungkan produktifitas dan fleksibilitas yang tinggi dari Sistem Manufaktur Transfer Line dan Job Shop. Pada riset ini pendekatan Activity-Based Costing (ABC digunakan sebagai bobot / weight dalam pencarian rute operasi pada mesin yang tepat, untuk lebih mengoptimasi biaya produksi secara keseluruhan. Adapun metode Searching yang digunakan adalah Simulated Annealing yang merupakan varian dari metode searching Hill Climbing. Waktu operasi ideal untuk memproses sebuah part digunakan sebagai Annealing Schedulenya. Dari hasil pengujian empiris dapat dibuktikan bahwa penggunaan pendekatan ABC dan Simulated Annealing untuk proses pencarian rute (routing dapat lebih
Theodorakos, I.; Zergioti, I.; Vamvakas, V.; Tsoukalas, D.; Raptis, Y. S.
2014-01-01
In this work, a picosecond diode pumped solid state laser and a nanosecond Nd:YAG laser have been used for the annealing and the partial nano-crystallization of an amorphous silicon layer. These experiments were conducted as an alternative/complementary to plasma-enhanced chemical vapor deposition method for fabrication of micromorph tandem solar cell. The laser experimental work was combined with simulations of the annealing process, in terms of temperature distribution evolution, in order to predetermine the optimum annealing conditions. The annealed material was studied, as a function of several annealing parameters (wavelength, pulse duration, fluence), as far as it concerns its structural properties, by X-ray diffraction, SEM, and micro-Raman techniques.
Theodorakos, I.; Zergioti, I.; Tsoukalas, D.; Raptis, Y. S., E-mail: yraptis@central.ntua.gr [Physics Department, National Technical University of Athens, Heroon Polytechniou 9, 15780 Zographou, Athens (Greece); Vamvakas, V. [Heliosphera SA, Industrial Area of Tripolis, 8th Building Block, 5th Road, GR-221 00 Tripolis (Greece)
2014-01-28
In this work, a picosecond diode pumped solid state laser and a nanosecond Nd:YAG laser have been used for the annealing and the partial nano-crystallization of an amorphous silicon layer. These experiments were conducted as an alternative/complementary to plasma-enhanced chemical vapor deposition method for fabrication of micromorph tandem solar cell. The laser experimental work was combined with simulations of the annealing process, in terms of temperature distribution evolution, in order to predetermine the optimum annealing conditions. The annealed material was studied, as a function of several annealing parameters (wavelength, pulse duration, fluence), as far as it concerns its structural properties, by X-ray diffraction, SEM, and micro-Raman techniques.
Speagle, Joshua S; Eisenstein, Daniel J; Masters, Daniel C; Steinhardt, Charles L
2015-01-01
Using a grid of $\\sim 2$ million elements ($\\Delta z = 0.005$) adapted from COSMOS photometric redshift (photo-z) searches, we investigate the general properties of template-based photo-z likelihood surfaces. We find these surfaces are filled with numerous local minima and large degeneracies that generally confound rapid but "greedy" optimization schemes, even with additional stochastic sampling methods. In order to robustly and efficiently explore these surfaces, we develop BAD-Z [Brisk Annealing-Driven Redshifts (Z)], which combines ensemble Markov Chain Monte Carlo (MCMC) sampling with simulated annealing to sample arbitrarily large, pre-generated grids in approximately constant time. Using a mock catalog of 384,662 objects, we show BAD-Z samples $\\sim 40$ times more efficiently compared to a brute-force counterpart while maintaining similar levels of accuracy. Our results represent first steps toward designing template-fitting photo-z approaches limited mainly by memory constraints rather than computation...
The Adaptive Multi-scale Simulation Infrastructure
Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)
2015-09-01
The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
Crystallization on a sphere using the simulated annealing algorithm implemented on H.P.C. systems
de Voogd, J. M.; Sloot, P. M. A.; Verbraeck, A.; Kerckhoffs, E.J.H.
1993-01-01
The research presented here is a comparison of the scalability of the simulated annealing algorithm on a vector super computer (CRAY Y-MP) with the scalability of a parallel implementation on a massively parallel transputer surface (Parsytec GCel with 512 nodes of typeT805). Some results of the annealing procedure applied to thecrystallization of Lennard-Jones particles on a sphere arepresented.
Hui Li; Xiong Wan; Taoli Liu; Zhongshou Liu; Yanhua Zhu
2007-01-01
Although emission spectral tomography (EST) combines emission spectral measurement with optical computed tomography (OCT), it is difficult to gain transient emission data from a large number of views,therefore, high precision OCT algorithms with few views ought to be studied for EST application. To improve the reconstruction precision in the case of few views, a new computed tomography reconstruction algorithm based on multipurpose optimal criterion and simulated annealing theory (multi-criterion simulated annealing reconstruction technique, MCSART) is proposed. This algorithm can suffice criterion of least squares, criterion of most uniformity, and criterion of most smoothness synchronously. We can get global optimal solution by MCSART algorithm with simulated annealing theory. The simulating experiment result shows that this algorithm is superior to the traditional algorithms under various noises.
Robot Path Planning Based on Simulated Annealing and Artificial Neural Networks
Xianmin Wei
2013-05-01
Full Text Available As for the limitations of algorithms in global path planning of mobile robot at present, this study applies the improved simulated annealing algorithm artificial neural networks to path planning of mobile robot in order to better the weaknesses of great scale of iteration computation and slow convergence, since the best-reserved simulated annealing algorithm was introduced and it was effectively combined with other algorithms, this improved algorithm has accelerated the convergence and shortened the computing time in the path planning and the global optimal solution can be quickly obtained. Because the simulated annealing algorithm was updated and the obstacle collision penalty function represented by neural networks and the path length are treated as the energy function, not only does the planning of path meet the standards of shortest path, but also avoids collisions with obstacles. Experimental results of simulation show this improved algorithm can effectively improve the calculation speed of path planning and ensure the quality of path planning.
Robot Path Planning Based on Simulated Annealing and Artificial Neural Networks
Xianmin Wei
2013-06-01
Full Text Available As for the limitations of algorithms in global path planning of mobile robot at present, this study applies the improved simulated annealing algorithm artificial neural networks to path planning of mobile robot in order to better the weaknesses of great scale of iteration computation and slow convergence, since the best-reserved simulated annealing algorithm was introduced and it was effectively combined with other algorithms, this improved algorithm has accelerated the convergence and shortened the computing time in the path planning and the global optimal solution can be quickly obtained. Because the simulated annealing algorithm was updated and the obstacle collision penalty function represented by neural networks and the path length are treated as the energy function, not only does the planning of path meet the standards of shortest path, but also avoids collisions with obstacles. Experimental results of simulation show this improved algorithm can effectively improve the calculation speed of path planning and ensure the quality of path planning.
Simulation of annealing process effect on texture evolution of deep-drawing sheet St15
Jinghong Sun; Yazheng Liu; Leyu Zhou
2005-01-01
A two-dimensional cellular automaton method was used to simulate grain growth during the recrystallization annealing of deep-drawing sheet Stl5, taking the simulated result of recrystallization and the experimental result of the annealing texture of deepdrawing sheet St15 as the initial condition and reference. By means of computer simulation, the microstructures and textures of different periods of grain growth were predicted. It is achieved that the grain size, shape and texture become stable after the grain growth at a constant temperature of 700℃ for 10 h, and the advantaged texture components { 111 } and { 111 } are dominant.
Zhu, Jiulong; Wang, Shijun
Presently water resource in most watersheds in China is distributed in terms of administrative instructions. This kind of allocation method has many disadvantages and hampers the instructional effect of market mechanism on water allocation. The paper studies South-to-North Water Transfer Project and discusses water allocation of the node lakes along the Project. Firstly, it advanced four assumptions. Secondly, it analyzed constraint conditions of water allocation in terms of present state of water allocation in China. Thirdly, it established a goal model of water allocation and set up a systematic model from the angle of comprehensive profits of water utilization and profits of the node lakes. Fourthly, it discussed calculation method of the model by means of Simulated Annealing Hybrid Genetic Algorithm (SHGA). Finally, it validated the rationality and validity of the model by a simulation testing.
Liang, Faming
2014-04-03
Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to use this much CPU time. This article proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation, it is shown that the new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, for example, a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors. Supplementary materials for this article are available online.
Laser annealing and simulation of amorphous silicon thin films for solar cell applications
Theodorakos, I.; Raptis, Y. S.; Vamvakas, V.; Tsoukalas, D.; Zergioti, I.
2014-03-01
In this work, a picosecond DPSS and a nanosecond Nd:YAG laser have been used for the annealing and the partial nanocrystallization of an amorphous silicon layer. These experiments were conducted in order to improve the characteristics of a micromorph tandem solar cell. The laser annealing was attempted at 1064nm in order to obtain the desired crystallization's depth and ratios. Preliminary annealing-processes, with different annealing parameters, have been tested, such as fluence, repetition rate and number of pulses. Irradiations were applied in the sub-melt regime, in order to prevent significant diffusion of p- and n-dopants to take place within the structure. The laser experimental work was combined with simulations of the laser annealing process, in terms of temperature distribution evolution, using the Synopsys Sentaurus Process TCAD software. The optimum annealing conditions for the two different pulse durations were determined. Experimentally determined optical properties of our samples, such as the absorption coefficient and reflectivity, were used for a more realistic simulation. From the simulations results, a temperature profile, appropriate to yield the desired recrystallization was obtained for the case of ps pulses, which was verified from the experimental results described below. The annealed material was studied, as far as it concerns its structural properties, by XRD, SEM and micro-Raman techniques, providing consistent information on the characteristics of the nanocrystalline material produced by the laser annealing experiments. It was found that, with the use of ps pulses, the resultant polycrystalline region shows crystallization's ratios similar to a PECVD developed poly-Silicon layer, with slightly larger nanocrystallite's size.
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Physical and mathematical models and numerical simulation of the diffusion of implanted impurities during rapid thermal treatment of silicon structures are discussed. The calculation results correspond to the experimental results with a sufficient accuracy. A simulation software system has been developed that is integrated into ATHENA simulation system developed by Silvaco Inc. This program can simulate processes of the low-energy implantation of B, BF2, P, As, Sb, C ions into the silicon structures and subsequent rapid thermal annealing. (authors)
Takahashi, Norio; Ebihara, Kenji; Yoshida, Koji; Nakata, Takayoshi; Ohashi, Ken; Miyata, Koji
1996-01-01
Factors affecting the convergence characteristics and results obtained by the optimal design method using the finite element method and simulated annealing are investigated systematically, and the optimal parameters for simulated annealing method are obtained. The optimal shape of the die mold for orientation of the magnetic powder (nonlinear magnetostatic problem) is obtained using finite elements and simulated annealing. The experimental verification is also carried out
Ruiz, Alfonso de la Fuente
2014-01-01
Brief description on the state of the art of some local optimization methods: Quantum annealing Quantum annealing (also known as alloy, crystallization or tempering) is analogous to simulated annealing but in substitution of thermal activation by quantum tunneling. The class of algorithmic methods for quantum annealing (dubbed: 'QA'), sometimes referred by the italian school as Quantum Stochastic Optimization ('QSO'), is a promising metaheuristic tool for solving local search problems in mult...
Optimization of pressurized water reactor shuffling by simulated annealing with heuristics
Simulated-annealing optimization of reactor core loading patterns is implemented with support for design heuristics during candidate pattern generation. The SIMAN optimization module uses the advanced nodal method of SIMULATE-3 and the full cross-section detail of CASMO-3 to evaluate accurately the neutronic performance of each candidate, resulting in high-quality patterns. The use of heuristics within simulated annealing is explored. Heuristics improve the consistency of optimization results for both fast- and slow-annealing runs with no penalty from the exclusion of unusual candidates. Thus, the heuristic application of designer judgment during automated pattern generation is shown to be effective. The capability of the SIMAN module to find and evaluate families of loading patterns that satisfy design constraints and have good objective performance within practical run times is demonstrated. The use of automated evaluations of successive cycles to explore multicycle effects of design decisions is discussed
Optimal actuator placement on an active reflector using a modified simulated annealing technique
Kuo, Chin-Po; Bruno, Robin
1991-01-01
The development of a lightweight actuation system for maintaining the surface accuracy of a composite honeycomb panel using piezoelectric actuators is discussed. A modified simulated annealing technique is used to optimize the problem with both combinatorial and continuous criteria and with inequality constraints. Near optimal solutions for the location of the actuators, using combinatorial optimization, and for the required actuator forces, employing continuous optimization, are sought by means of the modified simulated annealing technique. The actuator locations are determined by first seeking a near optimum solution using the modified simulated annealing technique. The final actuator configuration consists of an arrangement wherein the piezoelectric actuators are placed along six radial lines. Numerical results showing the achievable surface correction by means of this configuration are presented.
Simulated annealing algorithm for TSP%用模拟退火算法求解TSP
朱静丽
2011-01-01
货郎担问题，即TSP（Traveling Salesman Problem），是一个组合优化问题。具有NPC计算复杂性。本文分析了模拟退火算法模型，研究了用模拟退火算法求解TSP算法的可行性，并给出了用模拟退火算法求解TSP问题的具体实现方法。%Traveling salesman problem,that TSP（Travelling Salesman Problem）,is a combinatorial optimization problem.Computational complexity with the NPC.This paper analyzes the simulated annealing algorithm model to study the simulated annealing algorithm for TSP of the algorithm,and gives the simulated annealing algorithm for TSP on the specific implementation.
Sohn, Andrew; Biswas, Rupak
1996-01-01
Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a parallel synchronous simulated annealing method for solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing procedure, called Generalized Speculative Computation, which guarantees the same decision sequence as sequential simulated annealing. To demonstrate the performance of the parallel method, we have selected problem instances varying in size from 100-variables/425-clauses to 5000-variables/21,250-clauses. Experimental results on the AP1000 multiprocessor indicate that our approach can satisfy 99.9 percent of the clauses while giving almost a 70-fold speedup on 500 processors.
Sousa, Tiago M; Soares, Tiago; Morais, Hugo;
2016-01-01
The massive use of distributed generation and electric vehicles will lead to a more complex management of the power system, requiring new approaches to be used in the optimal resource scheduling field. Electric vehicles with vehicle-to-grid capability can be useful for the aggregator players in the...... mitigation of renewable sources intermittency and in the ancillary services procurement. In this paper, an energy and ancillary services joint management model is proposed. A simulated annealing approach is used to solve the joint management for the following day, considering the minimization of the...... aggregator total operation costs. The case study considers a distribution network with 33-bus, 66 distributed generation and 2000 electric vehicles. The proposed simulated annealing is matched with a deterministic approach allowing an effective and efficient comparison. The simulated annealing presents a...
Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations
Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias
2015-01-01
Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.
CHUShuchuan; JohnF.Roddick
2003-01-01
In this paper, a cluster generation algorithm for vector quantization using a tabu search approach with simulated annealing is proposed. The main iclea of this algorithm is to use the tabu search approach to gen-erate non-local moves for the clusters and apply the sim-ulated annealing technique to select the current best solu-tion, thus improving the cluster generation and reducing the mean squared error. Preliminary experimental results demonstrate that the proposed approach is superior to the tabu search approach with Generalised Lloyd algorithm.
Riaz, M. Tahir; Gutierrez Lopez, Jose Manuel; Pedersen, Jens Myrup;
2011-01-01
The paper presents a hybrid Genetic and Simulated Annealing algorithm for implementing Chordal Ring structure in optical backbone network. In recent years, topologies based on regular graph structures gained a lot of interest due to their good communication properties for physical topology of the...... networks. There have been many use of evolutionary algorithms to solve the problems which are in combinatory complexity nature, and extremely hard to solve by exact approaches. Both Genetic and Simulated annealing algorithms are similar in using controlled stochastic method to search the solution. The...
高红民; 周惠; 徐立中; 石爱业
2014-01-01
A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algorithm and multiple instance learning (MIL). The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13%at small training samples and the weaknesses of the conventional methods are overcome.
Liñán-García, Ernesto; Sánchez-Hernández, Juan Paulo; González-Barbosa, J. Javier; González-Flores, Carlos
2016-01-01
A new hybrid Multiphase Simulated Annealing Algorithm using Boltzmann and Bose-Einstein distributions (MPSABBE) is proposed. MPSABBE was designed for solving the Protein Folding Problem (PFP) instances. This new approach has four phases: (i) Multiquenching Phase (MQP), (ii) Boltzmann Annealing Phase (BAP), (iii) Bose-Einstein Annealing Phase (BEAP), and (iv) Dynamical Equilibrium Phase (DEP). BAP and BEAP are simulated annealing searching procedures based on Boltzmann and Bose-Einstein distributions, respectively. DEP is also a simulated annealing search procedure, which is applied at the final temperature of the fourth phase, which can be seen as a second Bose-Einstein phase. MQP is a search process that ranges from extremely high to high temperatures, applying a very fast cooling process, and is not very restrictive to accept new solutions. However, BAP and BEAP range from high to low and from low to very low temperatures, respectively. They are more restrictive for accepting new solutions. DEP uses a particular heuristic to detect the stochastic equilibrium by applying a least squares method during its execution. MPSABBE parameters are tuned with an analytical method, which considers the maximal and minimal deterioration of problem instances. MPSABBE was tested with several instances of PFP, showing that the use of both distributions is better than using only the Boltzmann distribution on the classical SA. PMID:27413369
Frausto-Solis, Juan; Liñán-García, Ernesto; Sánchez-Hernández, Juan Paulo; González-Barbosa, J Javier; González-Flores, Carlos; Castilla-Valdez, Guadalupe
2016-01-01
A new hybrid Multiphase Simulated Annealing Algorithm using Boltzmann and Bose-Einstein distributions (MPSABBE) is proposed. MPSABBE was designed for solving the Protein Folding Problem (PFP) instances. This new approach has four phases: (i) Multiquenching Phase (MQP), (ii) Boltzmann Annealing Phase (BAP), (iii) Bose-Einstein Annealing Phase (BEAP), and (iv) Dynamical Equilibrium Phase (DEP). BAP and BEAP are simulated annealing searching procedures based on Boltzmann and Bose-Einstein distributions, respectively. DEP is also a simulated annealing search procedure, which is applied at the final temperature of the fourth phase, which can be seen as a second Bose-Einstein phase. MQP is a search process that ranges from extremely high to high temperatures, applying a very fast cooling process, and is not very restrictive to accept new solutions. However, BAP and BEAP range from high to low and from low to very low temperatures, respectively. They are more restrictive for accepting new solutions. DEP uses a particular heuristic to detect the stochastic equilibrium by applying a least squares method during its execution. MPSABBE parameters are tuned with an analytical method, which considers the maximal and minimal deterioration of problem instances. MPSABBE was tested with several instances of PFP, showing that the use of both distributions is better than using only the Boltzmann distribution on the classical SA. PMID:27413369
Neutronic optimization in high conversion Th-233U fuel assembly with simulated annealing
This paper reports on fuel design optimization of a PWR operating in a self sustainable Th-233U fuel cycle. Monte Carlo simulated annealing method was used in order to identify the fuel assembly configuration with the most attractive breeding performance. In previous studies, it was shown that breeding may be achieved by employing heterogeneous Seed-Blanket fuel geometry. The arrangement of seed and blanket pins within the assemblies may be determined by varying the designed parameters based on basic reactor physics phenomena which affect breeding. However, the amount of free parameters may still prove to be prohibitively large in order to systematically explore the design space for optimal solution. Therefore, the Monte Carlo annealing algorithm for neutronic optimization is applied in order to identify the most favorable design. The objective of simulated annealing optimization is to find a set of design parameters, which maximizes some given performance function (such as relative period of net breeding) under specified constraints (such as fuel cycle length). The first objective of the study was to demonstrate that the simulated annealing optimization algorithm will lead to the same fuel pins arrangement as was obtained in the previous studies which used only basic physics phenomena as guidance for optimization. In the second part of this work, the simulated annealing method was used to optimize fuel pins arrangement in much larger fuel assembly, where the basic physics intuition does not yield clearly optimal configuration. The simulated annealing method was found to be very efficient in selecting the optimal design in both cases. In the future, this method will be used for optimization of fuel assembly design with larger number of free parameters in order to determine the most favorable trade-off between the breeding performance and core average power density. (authors)
Stochastic annealing simulation of copper under neutron irradiation
Heinisch, H.L. [Pacific Northwest National Lab., Richland, WA (United States); Singh, B.N. [Risoe National Lab., Roskilde (Denmark)
1998-03-01
This report is a summary of a presentation made at ICFRM-8 on computer simulations of defect accumulation during irradiation of copper to low doses at room temperature. The simulation results are in good agreement with experimental data on defect cluster densities in copper irradiated in RTNS-II.
Optimal design of hydraulic manifold blocks based on niching genetic simulated annealing algorithm
Jia Chunqiang; Yu Ling; Tian Shujun; Gao Yanming
2007-01-01
To solve the combinatorial optimization problem of outer layout and inner connection integrated schemes in the design of hydraulic manifold blocks(HMB),a hybrid genetic simulated annealing algorithm based on niche technology is presented.This hybrid algorithm,which combines genetic algorithm,simulated annealing algorithm and niche technology,has a strong capability in global and local search,and all extrema can be found in a short time without strict requests for preferences.For the complex restricted solid spatial layout problems in HMB,the optimizing mathematical model is presented.The key technologies in the integrated layout and connection design of HMB,including the realization of coding,annealing operation and genetic operation,are discussed.The framework of HMB optimal design system based on hybrid optimization strategy is proposed.An example is given to testify the effectiveness and feasibility of the algorithm.
Inverse planning in external beam radiotherapy often requires a scalar objective function that incorporates importance factors to mimic the planner's preferences between conflicting objectives. Defining those importance factors is not straightforward, and frequently leads to an iterative process in which the importance factors become variables of the optimization problem. In order to avoid this drawback of inverse planning, optimization using algorithms more suited to multiobjective optimization, such as evolutionary algorithms, has been suggested. However, much inverse planning software, including one based on simulated annealing developed at our institution, does not include multiobjective-oriented algorithms. This work investigates the performance of a modified simulated annealing algorithm used to drive aperture-based intensity-modulated radiotherapy inverse planning software in a multiobjective optimization framework. For a few test cases involving gastric cancer patients, the use of this new algorithm leads to an increase in optimization speed of a little more than a factor of 2 over a conventional simulated annealing algorithm, while giving a close approximation of the solutions produced by a standard simulated annealing. A simple graphical user interface designed to facilitate the decision-making process that follows an optimization is also presented
X-ray refinement of protein structures by simulated annealing: Test of the method on myohemerythrin
The recently developed method of structure factor refinement by molecular dynamics with simulated annealing is tested on the 118 residue protein myohemerythrin. A highly refined structure for this protein at 1.3/1.7 A resolution has recently been published. This is compared with the results of simulated annealing refinement (with no manual intervention) starting from an earlier model for the protein from a stage in the refinement when conventional least-squares methods could not improve the structure. Simulated annealing reduces the R factor at 2.5 A from 39 to 31%, with uniform temperature factors and no solvent molecules and with similar stereochemistry; the comparable value for the manually refined structure is 27.9%. Errors in backbone and sidechain positions up to about 3 A are corrected by the method. The error in backbone positions for roughly 85% of the initial structure is within this range, and in these regions the r.m.s. backbone error is reduced from 1.1 to 0.4 A. For the rest of the structure, including a region which was incorrectly built due to a sequence error, the procedure does not yield any improvement and manual intervention appears to be required. Nevertheless, the overall improvement in the structure results in electron density maps that are easier to interpret and permit identification of the errors in the structure. The general utility of the simulated annealing methodology in X-ray refinement is discussed. (orig.)
Crystallization on a sphere using the simulated annealing algorithm implemented on H.P.C. systems
J.M. Voogd; P.M.A. Sloot
1993-01-01
The research presented here is a comparison of the scalability of the simulated annealing algorithm on a vector super computer (CRAY Y-MP) with the scalability of a parallel implementation on a massively parallel transputer surface (Parsytec GCel with 512 nodes of typeT805). Some results of the anne
Computer-Assisted Scheduling of Army Unit Training: An Application of Simulated Annealing.
Hart, Roland J.; Goehring, Dwight J.
This report of an ongoing research project intended to provide computer assistance to Army units for the scheduling of training focuses on the feasibility of simulated annealing, a heuristic approach for solving scheduling problems. Following an executive summary and brief introduction, the document is divided into three sections. First, the Army…
Using genetic/simulated annealing algorithm to solve disassembly sequence planning
Wu Hao; Zuo Hongfu
2009-01-01
disassembly sequence.And the solution methodology based on the genetic/simulated annealing algorithm with binary-tree algorithm is given.Finally,an example is analyzed in detail,and the result shows that the model is correct and efficient.
MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing
Lindgreen, Stinus; Gardner, Paul P; Krogh, Anders
2007-01-01
multiple alignment of RNA sequences. Using Markov chain Monte Carlo in a simulated annealing framework, the algorithm MASTR (Multiple Alignment of STructural RNAs) iteratively improves both sequence alignment and structure prediction for a set of RNA sequences. This is done by minimizing a combined cost...
Improving Simulated Annealing by Recasting it as a Non-Cooperative Game
Wolpert, David; Bandari, Esfandiar; Tumer, Kagan
2001-01-01
The game-theoretic field of COllective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved "as a side-effect". Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed game-theory-motivated algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting improves simulated annealing by several orders of magnitude for spin glass relaxation and bin-packing.
Improving Simulated Annealing by Replacing Its Variables with Game-Theoretic Utility Maximizers
Wolpert, David H.; Bandari, Esfandiar; Tumer, Kagan
2001-01-01
The game-theory field of Collective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved as a side-effect. Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting significantly improves simulated annealing for a model of an economic process run over an underlying small-worlds topology. Furthermore, these experiments reveal novel small-worlds phenomena, and highlight the shortcomings of conventional mechanism design in bounded rationality domains.
A simulated annealing-based method for learning Bayesian networks from statistical data
Janžura, Martin; Nielsen, Jan
2006-01-01
Roč. 21, č. 3 (2006), s. 335-348. ISSN 0884-8173 R&D Projects: GA ČR GA201/03/0478 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian network * simulated annealing * Markov Chain Monte Carlo Subject RIV: BA - General Mathematics Impact factor: 0.429, year: 2006
Mori, Takaharu; Okamoto, Yuko
2009-10-01
Gramicidin A is a linear hydrophobic 15-residue peptide which consists of alternating D- and L-amino acids and forms a unique tertiary structure, called the β6.3-helix, to act as a cation-selective ion channel in the natural conditions. In order to investigate the intrinsic ability of the gramicidin A monomer to form secondary structures, we performed the folding simulation of gramicidin A using a simulated annealing molecular dynamics (MD) method in vacuum mimicking the low-dielectric, homogeneous membrane environment. The initial conformation was a fully extended one. From the 200 different MD runs, we obtained a right-handed β4.4-helix as the lowest-potential-energy structure, and left-handed β4.4-helix, right-handed and left-handed β6.3-helix as local-minimum energy states. These results are in accord with those of the experiments of gramicidin A in homogeneous organic solvent. Our simulations showed a slight right-hand sense in the lower-energy conformations and a quite β-sheet-forming tendency throughout almost the entire sequence. In order to examine the stability of the obtained right-handed β6.3-helix and β4.4-helix structures in more realistic membrane environment, we have also performed all-atom MD simulations in explicit water, ion, and lipid molecules, starting from these β-helix structures. The results suggested that β6.3-helix is more stable than β4.4-helix in the inhomogeneous, explicit membrane environment, where the pore water and the hydrogen bonds between Trp side-chains and lipid-head groups have a role to further stabilize the β6.3-helix conformation.
Estimation of Mutual Coupling Coefficient of the Array by Simulated Annealing Algorithm
GAO Huo-tao; ZHENG Xia; LI Yong-xu
2005-01-01
We propose a method for estimating the mutual coupling coefficient among antennas in this paper which is based on the principle of signal subspace and the simulated annealing (SA) algorithm. The computer simulation has been conducted to illustrate the excellent performance of this method and to demonstrate that it is statistically efficient. The benefit of this new method is that calibration signals and unknown signals can be received simultaneously, during the course of calibration.
Wang Hongkai; Guan Yanyong; Xue Peijun
2008-01-01
In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.
Annealing of dislocation loops in dislocation dynamics simulations
We report of 3-dimensional discrete dislocation dynamics (DDD) simulations of dislocation loops coarsening by vacancy bulk diffusion. The calculation is based upon a model which couples the diffusion theory of vacancies to the DDD in order to obtain the climb rate of the dislocation segments. Calculation of isolated loops agrees with experimental observations, i.e. loops shrink or expand, depending on their type and vacancy supersaturation. When an array of dislocation loops of various sizes is considered, and the total number of vacancies in the simulation is maintained constant, the largest dislocations are found to increase in size at the expense of small ones, which disappear in a process known as Ostwald ripening.
Annealing of dislocation loops in dislocation dynamics simulations
Mordehai, Dan; Clouet, Emmanuel [SRMP, CEA-Saclay, 91191 Gif-sur-Yvette Cedex (France); Fivel, Marc; Verdier, Marc, E-mail: danmord@tx.technion.ac.il [CNRS/SIMAP, INPG, BP 75, 38402 St Martin d' Heres (France)
2009-07-15
We report of 3-dimensional discrete dislocation dynamics (DDD) simulations of dislocation loops coarsening by vacancy bulk diffusion. The calculation is based upon a model which couples the diffusion theory of vacancies to the DDD in order to obtain the climb rate of the dislocation segments. Calculation of isolated loops agrees with experimental observations, i.e. loops shrink or expand, depending on their type and vacancy supersaturation. When an array of dislocation loops of various sizes is considered, and the total number of vacancies in the simulation is maintained constant, the largest dislocations are found to increase in size at the expense of small ones, which disappear in a process known as Ostwald ripening.
Destya Arisetyanti
2012-09-01
Full Text Available Standar Digital Video Broadcasting Terrestrial (DVB-T diimplementasikan pada konfigurasi Single Frequency Network (SFN dimana seluruh pemancar pada sebuah jaringan beroperasi pada kanal frekuensi yang sama dan ditransmisikan pada waktu yang sama. SFN lebih dipilih daripada sistem pendahulunya yaitu Multi Frequency Network (MFN karena menggunakan frekuensi yang lebih efisien serta jangkauan area cakupan yang lebih luas. Pada sisi penerima memungkinkan adanya skenario multipath dengan menggabungkan sinyal dari pemancar yang berbeda karena konfigurasi SFN ini berbasis Orthogonal Frequency Division Multiplexing (OFDM. Pada penelitian ini, data ketinggian dan jumlah gedung melalui model prediksi propagasi free space dan knife edge akan diterapkan untuk memperkirakan nilai daya terima dan delay sinyal. Perhitungan nilai carrier (C dan carrier to interference (C/I dilakukan untuk mengetahui kualitas sinyal pada sisi penerima. Selanjutnya, optimasi parameter lokasi pemancar diterapkan oleh algoritma Simulated Annealing dengan menggunakan tiga cooling schedule terbaik. Simulated Annealing merupakan algoritma optimasi berdasarkan sistem termodinamika yang mensimulasikan proses annealing. Simulated Annealing telah berhasil memperluas daerah cakupan SFN. Hal ini dibuktikan dengan berkurangnya sebagian besar titik receiver dengan kualitas sinyal dibawah threshold.
Experiences with serial and parallel algorithms for channel routing using simulated annealing
Brouwer, Randall Jay
1988-01-01
Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.
Annealing simulations of nano-sized amorphous structures in Sic
A two-dimensional model of a nano-sized amorphous layer embedded in a perfect crystal has been developed, and the amorphous-to-crystalline (a-c) transition in 3C-Sic at 2000 K has been studied using molecular dynamics methods, with simulation times of up to 88 ns. Analysis of the a-c interfaces reveals that the recovery of the bond defects existing at the a-c interfaces plays an important role in recrystallization. During the recrystallization process, a second ordered phase, crystalline 2H-SiC, nucleates and grows, and this phase is stable for long simulation times. The crystallization mechanism is a two-step process that is separated by a longer period of second-phase stability. The kink sites formed at the interfaces between 2H- and 3C-SiC provide a low energy path for 2H-SiC atoms to transfer to 3C-SiC atoms, a process which can be defined as a solid-phase epitaxial transformation (SPET). It is observed that the nano-sized amorphous structure can be fully recrystallized at 2000 K in SiC, which is in agreement with experimental observations
Sheng Lu
2015-01-01
Full Text Available To solve the problem of parameter selection during the design of magnetically coupled resonant wireless power transmission system (MCR-WPT, this paper proposed an improved genetic simulated annealing algorithm. Firstly, the equivalent circuit of the system is analysis in this study and a nonlinear programming mathematical model is built. Secondly, in place of the penalty function method in the genetic algorithm, the selection strategy based on the distance between individuals is adopted to select individual. In this way, it reduces the excess empirical parameters. Meanwhile, it can improve the convergence rate and the searching ability by calculating crossover probability and mutation probability according to the variance of population’s fitness. At last, the simulated annealing operator is added to increase local search ability of the method. The simulation shows that the improved method can break the limit of the local optimum solution and get the global optimum solution faster. The optimized system can achieve the practical requirements.
Szu, Harold H.
1993-09-01
Classical artificial neural networks (ANN) and neurocomputing are reviewed for implementing a real time medical image diagnosis. An algorithm known as the self-reference matched filter that emulates the spatio-temporal integration ability of the human visual system might be utilized for multi-frame processing of medical imaging data. A Cauchy machine, implementing a fast simulated annealing schedule, can determine the degree of abnormality by the degree of orthogonality between the patient imagery and the class of features of healthy persons. An automatic inspection process based on multiple modality image sequences is simulated by incorporating the following new developments: (1) 1-D space-filling Peano curves to preserve the 2-D neighborhood pixels' relationship; (2) fast simulated Cauchy annealing for the global optimization of self-feature extraction; and (3) a mini-max energy function for the intra-inter cluster-segregation respectively useful for top-down ANN designs.
DKIST Adaptive Optics System: Simulation Results
Marino, Jose; Schmidt, Dirk
2016-05-01
The 4 m class Daniel K. Inouye Solar Telescope (DKIST), currently under construction, will be equipped with an ultra high order solar adaptive optics (AO) system. The requirements and capabilities of such a solar AO system are beyond those of any other solar AO system currently in operation. We must rely on solar AO simulations to estimate and quantify its performance.We present performance estimation results of the DKIST AO system obtained with a new solar AO simulation tool. This simulation tool is a flexible and fast end-to-end solar AO simulator which produces accurate solar AO simulations while taking advantage of current multi-core computer technology. It relies on full imaging simulations of the extended field Shack-Hartmann wavefront sensor (WFS), which directly includes important secondary effects such as field dependent distortions and varying contrast of the WFS sub-aperture images.
An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities
Amer, Hayder; Salman, Naveed; Hawes, Matthew; Chaqfeh, Moumena; Mihaylova, Lyudmila; Mayfield, Martin
2016-01-01
Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads’ length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario. PMID:27376289
An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities.
Amer, Hayder; Salman, Naveed; Hawes, Matthew; Chaqfeh, Moumena; Mihaylova, Lyudmila; Mayfield, Martin
2016-01-01
Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads' length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO₂ emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario. PMID:27376289
An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities
Hayder Amer
2016-06-01
Full Text Available Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads’ length are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario.
Dao-Wei Bi
2007-05-01
Full Text Available The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, we focus on energy-efficient coverage with distributed particle swarm optimization and simulated annealing. First, the energy-efficient coverage problem is formulated with sensing coverage and energy consumption models. We consider the network composed of stationary and mobile nodes. Second, coverage and energy metrics are presented to evaluate the coverage rate and energy consumption of a wireless sensor network, where a grid exclusion algorithm extracts the coverage state and DijkstraÃ¢Â€Â™s algorithm calculates the lowest cost path for communication. Then, a hybrid algorithm optimizes the energy consumption, in which particle swarm optimization and simulated annealing are combined to find the optimal deployment solution in a distributed manner. Simulated annealing is performed on multiple wireless sensor nodes, results of which are employed to correct the local and global best solution of particle swarm optimization. Simulations of wireless sensor node deployment verify that coverage performance can be guaranteed, energy consumption of communication is conserved after deployment optimization and the optimization performance is boosted by the distributed algorithm. Moreover, it is demonstrated that energy efficiency of wireless sensor networks is enhanced by the proposed optimization algorithm in target tracking applications.
Wrożyna, Andrzej; Pernach, Monika; Kuziak, Roman; Pietrzyk, Maciej
2016-04-01
Due to their exceptional strength properties combined with good workability the Advanced High-Strength Steels (AHSS) are commonly used in automotive industry. Manufacturing of these steels is a complex process which requires precise control of technological parameters during thermo-mechanical treatment. Design of these processes can be significantly improved by the numerical models of phase transformations. Evaluation of predictive capabilities of models, as far as their applicability in simulation of thermal cycles thermal cycles for AHSS is considered, was the objective of the paper. Two models were considered. The former was upgrade of the JMAK equation while the latter was an upgrade of the Leblond model. The models can be applied to any AHSS though the examples quoted in the paper refer to the Dual Phase (DP) steel. Three series of experimental simulations were performed. The first included various thermal cycles going beyond limitations of the continuous annealing lines. The objective was to validate models behavior in more complex cooling conditions. The second set of tests included experimental simulations of the thermal cycle characteristic for the continuous annealing lines. Capability of the models to describe properly phase transformations in this process was evaluated. The third set included data from the industrial continuous annealing line. Validation and verification of models confirmed their good predictive capabilities. Since it does not require application of the additivity rule, the upgrade of the Leblond model was selected as the better one for simulation of industrial processes in AHSS production.
Simulations of the effect of pulse annealing on optically-stimulated luminescence of quartz
Pulse annealing techniques are commonly used in OSL studies of quartz to obtain information on the kinetic parameters of OSL traps and hole reservoirs. In this paper, simulations of pulse annealing experiments are carried out using the comprehensive model for quartz developed by Bailey [2001. Towards a general kinetic model for optically and thermally stimulated luminescence of quartz. Radiat. Meas. 33, 17-45] for both natural and laboratory irradiated aliquots. The results of the simulations are in qualitative agreement with, and reproduce, several unusual features of the experimental data of Wintle and Murray [1998. Towards the development of a preheat procedure for OSL dating of quartz. Radiat. Meas. 29, 81-94]. The simulations are also carried out using different heating rates, and show that pulse annealing experiments can be used to recover appropriate kinetic parameters for both the OSL traps and the hole reservoirs known to exist in quartz. The results of the simulations show the importance of these hole reservoirs in determining how the OSL signal depends upon the preheat temperature
Pereira, Ana I.; Lima, José; Costa, Paulo
2013-10-01
There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The presented paper addresses a comparison between two optimization methods, the Stretched Simulated Annealing and the Genetic Algorithm, that runs in an accurate and stable simulation model. Final results show the comparative study and demonstrate that optimization is a valid gait planning technique.
Adaptive Optics Simulations for Siding Spring
Goodwin, Michael; Lambert, Andrew
2012-01-01
Using an observational derived model optical turbulence profile (model-OTP) we have investigated the performance of Adaptive Optics (AO) at Siding Spring Observatory (SSO), Australia. The simulations cover the performance for AO techniques of single conjugate adaptive optics (SCAO), multi-conjugate adaptive optics (MCAO) and ground-layer adaptive optics (GLAO). The simulation results presented in this paper predict the performance of these AO techniques as applied to the Australian National University (ANU) 2.3 m and Anglo-Australian Telescope (AAT) 3.9 m telescopes for astronomical wavelength bands J, H and K. The results indicate that AO performance is best for the longer wavelengths (K-band) and in the best seeing conditions (sub 1-arcsecond). The most promising results are found for GLAO simulations (field of view of 180 arcsecs), with the field RMS for encircled energy 50% diameter (EE50d) being uniform and minimally affected by the free-atmosphere turbulence. The GLAO performance is reasonably good over...
Fast and accurate protein substructure searching with simulated annealing and GPUs
Stivala Alex D
2010-09-01
Full Text Available Abstract Background Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif searching. Results We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU. Conclusions The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.
The generalized simulated annealing algorithm in the low energy electron diffraction search problem
We present in this work results concerning the application of the generalized simulated annealing (GSA) algorithm to the LEED search problem. The influence of the visiting distribution function (defined by the so-called qV parameter) in the effectiveness of the method was investigated by the application of the algorithm to structural searches for optimization of two to ten parameters in a theory-theory comparison for the CdTe(110) system. Results, obtained with the scaling relation and probability of convergence as a function of the number of parameters to be varied, indicate the fast simulated annealing (FSA) (qV = 2.0) approach as the best search machine
Jin Shi-Feng; Wang Wei-Min; Zhou Jian-Kun; Guo Hong-Xuan; J.F. Webb; Bian Xiu-Fang
2005-01-01
The nanocrystallization behaviour of Zr70Cu20Ni10 metallic glass during isothermal annealing is studied by employing a Monte Carlo simulation incorporating with a modified Ising model and a Q-state Potts model. Based on the simulated microstructure and differential scanning calorimetry curves, we find that the low crystal-amorphous interface energy of Ni plays an important role in the nanocrystallization of primary Zr2Ni. It is found that when T ＜ TImax (where TImax is the temperature with maximum nucleation rate), the increase of temperature results in a larger growth rate and a much finer microstructure for the primary Zr2Ni, which accords with the microstructure evolution in "flash annealing". Finally, the Zr2Ni/Zr2Cu interface energy σG contributes to the pinning effect of the primary nano-sized Zr2Ni grains in the later formed normal Zr2Cu grains.
Optimizing the natural connectivity of scale-free networks using simulated annealing
Duan, Boping; Liu, Jing; Tang, Xianglong
2016-09-01
In real-world networks, the path between two nodes always plays a significant role in the fields of communication or transportation. In some cases, when one path fails, the two nodes cannot communicate any more. Thus, it is necessary to increase alternative paths between nodes. In the recent work (Wu et al., 2011), Wu et al. proposed the natural connectivity as a novel robustness measure of complex networks. The natural connectivity considers the redundancy of alternative paths in a network by computing the number of closed paths of all lengths. To enhance the robustness of networks in terms of the natural connectivity, in this paper, we propose a simulated annealing method to optimize the natural connectivity of scale-free networks without changing the degree distribution. The experimental results show that the simulated annealing method clearly outperforms other local search methods.
Optimización Global Simulated Annealing
Francisco Sánchez Mares
2006-01-01
Full Text Available El presente trabajo muestra la aplicación del método de optimización global Simulated Annealing (SA. Esta técnica ha sido aplicada en diversas áreas de la ingeniería como una estrategia robusta y versátil para calcular con éxito el mínimo global de una función o un sistema de funciones. Para probar la eficiencia del método se encontraron los mínimos globales de una función arbitraria y se evaluó el comportamiento numérico del Simulated Annealing durante la convergencia a las dos soluciones que presenta el caso de estudio.
吴剑锋; 朱学愚; 刘建立
1999-01-01
The genetic algorithm (GA) is a global and random search procedure based on the mechanics of natural selection and natural genetics. A new optimization method of the genetic algorithm-based simulated annealing penalty function (GASAPF) is presented to solve groundwater management model. Compared with the traditional gradient-based algorithms, the GA is straightforward and there is no need to calculate derivatives of the objective function. The GA is able to generate both convex and nonconvex points within the feasible region. It can be sure that the GA converges to the global or at least near-global optimal solution to handle the constraints by simulated annealing technique. Maximum pumping example results show that the GASAPF to solve optimization model is very efficient and robust.
Hand Motion Tracking Using Simulated Annealing Method in a Discrete Space
LIANG Wei; JIA Yun-de; LIU Tang-li; HAN Lei; WU Xin-xiao
2007-01-01
Hand tracking is a challenging problem due to the complexity of searching in a 20 + degrees of freedom (DOF) space for an optimal estimation of hand configuration.The feasible hand configurations are represented as a discrete space,which avoids learning to find parameters as general configuration space representations do.Then,an extended simulated annealing method with particle filtering to search for optimal hand configuration in the proposed discrete space,in which simplex search running in multi-processor is designed to predict the hand motion instead of initializing the simulated annealing randomly,and particle filtering is employed to represent the state of the tracker at each layer for searching in high dimensional configuration space.Experimental results show that the proposed method makes the hand tracking more efficient and robust.
Use of simulated annealing in standardization and optimization of the acerola wine production
Sheyla dos Santos Almeida
2014-06-01
Full Text Available In this study, seven wine samples were prepared varying the amount of pulp of acerola fruits and the sugar content using the simulated annealing technique to obtain the optimal sensory qualities and cost for the wine produced. S. cerevisiae yeast was used in the fermentation process and the sensory attributes were evaluated using a hedonic scale. Acerola wines were classified as sweet, with 11°GL of alcohol concentration and with aroma, taste, and color characteristics of the acerola fruit. The simulated annealing experiments showed that the best conditions were found at mass ratio between 1/7.5-1/6 and total soluble solids between 28.6-29.0 °Brix, from which the sensory acceptance scores of 6.9, 6.8, and 8.8 were obtained for color, aroma, and flavor, respectively, with a production cost 43-45% lower than the cost of traditional wines commercialized in Brazil.
Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization
Supriya Dhabal; Palaniandavar Venkateswaran
2014-01-01
We present a novel hybrid algorithm based on particle swarm optimization (PSO) and simulated annealing (SA) for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The exper...
Dao-Wei Bi; Sheng Wang; Jun-Jie Ma; Xue Wang
2007-01-01
The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, we focus on energy-efficient coverage with distributed particle swarm optimization and simulated annealing. First, the energy-efficient coverage problem is formulated with sensing coverage and energy consumption models. We consider the network composed of stationary and mobile nodes. Second, coverage and energy metrics are presented to evaluate the coverage...
Sirisumrannukul, Somporn
2010-01-01
The network reconfiguration problem for reliability enhancement is solved by the developed simulated annealing in conjunction with reliability worth analysis that provides an indirect measure for cost implication associated with power failure. The objective is to minimize customer interruption cost with the constraints that all load points have to be electrically supplied and radially connected. It can be seen from the results of the RBTS and the 69-bus system that the total customer interrup...
EXTRUSION DIE PROFILE DESIGN USING SIMULATED ANNEALING ALGORITHM AND PARTICLE SWARM OPTIMIZATION
R.VENKETESAN
2010-01-01
In this paper a new method has been proposed for optimum shape design of extrusion die. The Design problem is formulated as an unconstrained optimization problem. Here nontraditional optimization techniques likeSimulated Annealing Algorithm and Particle Swarm Optimization are used to minimize the extrusion force by optimizing the extrusion ratio and die cone angle. Internal power of deformation is also calculated and results are compared.
Design of prestressed concrete precast road bridges with hybrid simulated annealing
Martí Albiñana, José Vicente; Gonzalez Vidosa, Fernando; Yepes Piqueras, Víctor; Alcalá González, Julián
2013-01-01
This paper describes one approach to the analysis and design of prestressed concrete precast road bridges, with double U-shaped cross-section and isostatic spans. The procedure used to solve the combinatorial problem is a variant of simulated annealing with a neighborhood move based on the mutation operator from the genetic algorithms (SAMO). This algorithm is applied to the economic cost of these structures at different stages of manufacturing, transportation and construction. The problem in...
Čapek, P.; Hejtmánek, Vladimír; Brabec, Libor; Zikánová, Arlette; Kočiřík, Milan
2009-01-01
Roč. 76, č. 2 (2009), s. 179-198. ISSN 0169-3913 R&D Projects: GA ČR GA203/05/0347 Institutional research plan: CEZ:AV0Z40720504; CEZ:AV0Z40400503 Keywords : stochastic reconstruction * simulated annealing * two-point cluster function Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 0.966, year: 2009
Paul, Gerald
2010-01-01
For almost two decades the question of whether tabu search (TS) or simulated annealing (SA) performs better for the quadratic assignment problem has been unresolved. To answer this question satisfactorily, we compare performance at various values of targeted solution quality, running each heuristic at its optimal number of iterations for each target. We find that for a number of varied problem instances, SA performs better for higher quality targets while TS performs better for lower quality targets.
EXTRUSION DIE PROFILE DESIGN USING SIMULATED ANNEALING ALGORITHM AND PARTICLE SWARM OPTIMIZATION
R.VENKETESAN
2010-08-01
Full Text Available In this paper a new method has been proposed for optimum shape design of extrusion die. The Design problem is formulated as an unconstrained optimization problem. Here nontraditional optimization techniques likeSimulated Annealing Algorithm and Particle Swarm Optimization are used to minimize the extrusion force by optimizing the extrusion ratio and die cone angle. Internal power of deformation is also calculated and results are compared.
Minimizing distortion and internal forces in truss structures by simulated annealing
Kincaid, Rex K.; Padula, Sharon L.
1990-01-01
Inaccuracies in the length of members and the diameters of joints of large space structures may produce unacceptable levels of surface distortion and internal forces. Here, two discrete optimization problems are formulated, one to minimize surface distortion (DSQRMS) and the other to minimize internal forces (FSQRMS). Both of these problems are based on the influence matrices generated by a small-deformation linear analysis. Good solutions are obtained for DSQRMS and FSQRMS through the use of a simulated annealing heuristic.
A Simulated Annealing Algorithm for the Optimization of Multistage Depressed Collector Efficiency
Vaden, Karl R.; Wilson, Jeffrey D.; Bulson, Brian A.
2002-01-01
The microwave traveling wave tube amplifier (TWTA) is widely used as a high-power transmitting source for space and airborne communications. One critical factor in designing a TWTA is the overall efficiency. However, overall efficiency is highly dependent upon collector efficiency; so collector design is critical to the performance of a TWTA. Therefore, NASA Glenn Research Center has developed an optimization algorithm based on Simulated Annealing to quickly design highly efficient multi-stage depressed collectors (MDC).
Application of simulated annealing to the biclustering of gene expression data
Bolshakova, Nadia; Cunningham, Padraig
2006-01-01
In a gene expression data matrix, a bicluster is a submatrix of genes and conditions that exhibits a high correlation of expression activity across both rows and columns. The problem of locating the most significant bicluster has been shown to be NP-complete. Heuristic approaches such as Cheng and Church?s greedy node deletion algorithm have been previously employed. It is to be expected that stochastic search techniques such as evolutionary algorithms or simulated anneal...
Dong Yunfeng
2013-01-01
The scheduling problem is a typical time table problem in educational administration. For such a NP complete problems, when the genetic algorithm solves this problem, it has precociousness phenomenon and quickly converges not to the global optimal solution but to the local optimal solution. Therefore, we use the advantage of simulated annealing algorithm to transform the fitness function and chaotic sequence to control the crossover and mutation genetic ope...
A Phoenix++ Based New Genetic Algorithm Involving Mechanism of Simulated Annealing
Luokai Hu; Jin Liu; Chao Liang; Fuchuan Ni; Hang Chen
2015-01-01
Genetic algorithm is easy to fall into local optimal solution. Simulated annealing algorithm may accept nonoptimal solution at a certain probability to jump out of local optimal solution. On the other hand, lack of communication among genes in MapReduce platform based genetic algorithm, the high-performance distributed computing technologies or platforms can further increase the execution efficiency of these traditional genetic algorithms. To this end, we propose a novel Phoenix++ based new g...
SIMULATED ANNEALING ALGORITHM FOR SCHEDULING DIVISIBLE LOAD IN LARGE SCALE DATA GRIDS
Monir Abdullah; Mohamed, Othman; Hamidah Ibrahim; Shamala Subramaniam
2010-01-01
In many data grid applications, data can be decomposed into multiple independent sub datasets and distributed for parallel execution and analysis. This property has been successfully exploited using Divisible Load Theory (DLT). Many Scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. SA algorithm is integrated with DLT model and compared with th...
Optimal design of a DC MHD pump by simulated annealing method
Bouali Khadidja
2014-01-01
Full Text Available In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.
Hussain, Faraz; Jha, Sumit K.; Jha, Susmit; Langmead, Christopher J.
2014-01-01
Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential ...
A parallel simulated annealing algorithm for standard cell placement on a hypercube computer
Jones, Mark Howard
1987-01-01
A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.
Validation of Sensor-Directed Spatial Simulated Annealing Soil Sampling Strategy.
Scudiero, Elia; Lesch, Scott M; Corwin, Dennis L
2016-07-01
Soil spatial variability has a profound influence on most agronomic and environmental processes at field and landscape scales, including site-specific management, vadose zone hydrology and transport, and soil quality. Mobile sensors are a practical means of mapping spatial variability because their measurements serve as a proxy for many soil properties, provided a sensor-soil calibration is conducted. A viable means of calibrating sensor measurements over soil properties is through linear regression modeling of sensor and target property data. In the present study, two sensor-directed, model-based, sampling scheme delineation methods were compared to validate recent applications of soil apparent electrical conductivity (EC)-directed spatial simulated annealing against the more established EC-directed response surface sampling design (RSSD) approach. A 6.8-ha study area near San Jacinto, CA, was surveyed for EC, and 30 soil sampling locations per sampling strategy were selected. Spatial simulated annealing and RSSD were compared for sensor calibration to a target soil property (i.e., salinity) and for evenness of spatial coverage of the study area, which is beneficial for mapping nontarget soil properties (i.e., those not correlated with EC). The results indicate that the linear modeling EC-salinity calibrations obtained from the two sampling schemes provided salinity maps characterized by similar errors. The maps of nontarget soil properties show similar errors across sampling strategies. The Spatial Simulated Annealing methodology is, therefore, validated, and its use in agronomic and environmental soil science applications is justified. PMID:27380070
Zhao, Yi; Cao, Xiangyu; Gao, Jun; Sun, Yu; Yang, Huanhuan; Liu, Xiao; Zhou, Yulong; Han, Tong; Chen, Wei
2016-01-01
We propose a new strategy to design broadband and wide angle diffusion metasurfaces. An anisotropic structure which has opposite phases under x- and y-polarized incidence is employed as the “0” and “1” elements base on the concept of coding metamaterial. To obtain a uniform backward scattering under normal incidence, Simulated Annealing algorithm is utilized in this paper to calculate the optimal layout. The proposed method provides an efficient way to design diffusion metasurface with a simple structure, which has been proved by both simulations and measurements. PMID:27034110
Zhao, Yi; Cao, Xiangyu; Gao, Jun; Sun, Yu; Yang, Huanhuan; Liu, Xiao; Zhou, Yulong; Han, Tong; Chen, Wei
2016-04-01
We propose a new strategy to design broadband and wide angle diffusion metasurfaces. An anisotropic structure which has opposite phases under x- and y-polarized incidence is employed as the “0” and “1” elements base on the concept of coding metamaterial. To obtain a uniform backward scattering under normal incidence, Simulated Annealing algorithm is utilized in this paper to calculate the optimal layout. The proposed method provides an efficient way to design diffusion metasurface with a simple structure, which has been proved by both simulations and measurements.
Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier
2009-01-01
The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989
Simulated Annealing Study on Structures and Energetics of CO2 in Argon Clusters
Le-cheng Wang; Dai-qian Xie
2011-01-01
The minimum-energy configurations and energetic properties of the ArN-CO2 (N=1-19) van der Waals clusters were investigated by a simulated annealing algorithm.A newly developed Ar-CO2 potential energy surface together with the Aziz Ar-Ar interaction potential was employed to construct the high dimensional potential functions by pairwise additive approximation.The global minimal conformations were optimized by sampling the glassy phase space with a circumspectively formulated annealing schedule.Unlike the lighter RgN-CO2 clusters,the size-dependent structural and energetic characteristics of ArN-CO2 exhibit a different behavior.The dramatically variations with number of solvent were found for small clusters.After the completion of the first solvation shell at N=17,the clusters were evolved more smoothly.
Computer simulations of randomly branching polymers: annealed versus quenched branching structures
Rosa, Angelo; Everaers, Ralf
2016-08-01
We present computer simulations of three systems of randomly branching polymers in d = 3 dimensions: ideal trees and self-avoiding trees with annealed and quenched connectivities. In all cases, we performed a detailed analysis of trees connectivities, spatial conformations and statistical properties of linear paths on trees, and compare the results to the corresponding predictions of Flory theory. We confirm that, overall, the theory predicts correctly that trees with quenched ideal connectivity exhibit less overall swelling in good solvent than corresponding trees with annealed connectivity even though they are more strongly stretched on the path level. At the same time, we emphasize the inadequacy of the Flory theory in predicting the behaviour of other, and equally relevant, observables like contact probabilities between tree nodes. We show, then, that contact probabilities can be aptly characterized by introducing a novel critical exponent, {θ }{path}, which accounts for how they decay as a function of the node-to-node path distance on the tree.
Martinez-Limia, A. [Fraunhofer Institute of Integrated Systems and Device Technology, Schottkystrasse 10, 91058 Erlangen (Germany); Pichler, P. [Fraunhofer Institute of Integrated Systems and Device Technology, Schottkystrasse 10, 91058 Erlangen (Germany); Chair of Electron Devices, University of Erlangen-Nuremberg, Cauerstrasse 6, 91058 Erlangen (Germany)], E-mail: peter.pichler@iisb.fraunhofer.de; Lerch, W.; Paul, S. [Mattson Thermal Products GmbH, Daimlerstrasse 10, 89160 Dornstadt (Germany); Kheyrandish, H. [CSMA - MATS, Queens Road, Stoke on Trent ST4 7LQ (United Kingdom); Pakfar, A.; Tavernier, C. [STMicroelectronics SA, 850 rue Jean Monnet, 38926 Crolles (France)
2008-12-05
The possibility of using solid phase epitaxial regrowth (SPER) for activation of arsenic after amorphizing implantation in silicon is explored in this contribution and compared to spike annealing and published flash-annealing experiments. SPER takes advantage of the high activation level of the dopants after SPER combined with practically no dopant diffusion. We performed implantation and annealing experiments for three combinations of implantation energy and dose, and compared the results of SPER and spike annealing. The thermal stability of the dopant distribution was studied by subsequent post-annealing treatment for temperatures between 750 deg. C and 900 deg. C. The results of these experiments were included in the calibration of a diffusion and activation model for arsenic with high predictive capabilities. Additional simulations over a wide range of implantation energies were done to compare the efficiency of SPER, spike and flash annealing. The specific contributions to deactivation via different processes like clustering, precipitation, and segregation are discussed and annealing strategies to minimize the deactivation are proposed. Spike annealing seems to be the best solution for junctions of 25 nm or deeper, while for shallower junctions other processes combining preamorphization, multiple implantation steps, SPER, and/or flash annealing are needed.
Adaptive System Modeling for Spacecraft Simulation
Thomas, Justin
2011-01-01
This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).
The results of object kinetic Monte Carlo (OKMC) simulations of the annealing of primary cascade damage in bulk tungsten using a comprehensive database of cascades obtained from molecular dynamics (Setyawan et al.) are described as a function of primary knock-on atom (PKA) energy at temperatures of 300, 1025 and 2050 K. An increase in SIA clustering coupled with a decrease in vacancy clustering with increasing temperature, in addition to the disparate mobilities of SIAs versus vacancies, causes an interesting effect of temperature on cascade annealing. The annealing efficiency (the ratio of the number of defects after and before annealing) exhibits an inverse U-shape curve as a function of temperature. The capabilities of the newly developed OKMC code KSOME (kinetic simulations of microstructure evolution) used to carry out these simulations are described
Adaptive wavelet simulation of global ocean dynamics
N. K.-R. Kevlahan
2015-07-01
Full Text Available In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method for the rotating shallow water equations on the sphere with bathymetry and coastline data from NOAA's ETOPO1 database. This code could form the dynamical core for a future global ocean model. The potential of the dynamically adaptive ocean model is illustrated by using it to simulate the 2004 Indonesian tsunami and wind-driven gyres.
Kumar, Pushpendra; Huber, Patrick
2016-04-01
Discovery of porous silicon formation in silicon substrate in 1956 while electro-polishing crystalline Si in hydrofluoric acid (HF), has triggered large scale investigations of porous silicon formation and their changes in physical and chemical properties with thermal and chemical treatment. A nitrogen sorption study is used to investigate the effect of thermal annealing on electrochemically etched mesoporous silicon (PS). The PS was thermally annealed from 200˚C to 800˚C for 1 hr in the presence of air. It was shown that the pore diameter and porosity of PS vary with annealing temperature. The experimentally obtained adsorption / desorption isotherms show hysteresis typical for capillary condensation in porous materials. A simulation study based on Saam and Cole model was performed and compared with experimentally observed sorption isotherms to study the physics behind of hysteresis formation. We discuss the shape of the hysteresis loops in the framework of the morphology of the layers. The different behavior of adsorption and desorption of nitrogen in PS with pore diameter was discussed in terms of concave menisci formation inside the pore space, which was shown to related with the induced pressure in varying the pore diameter from 7.2 nm to 3.4 nm.
Simulated annealing algorithm for solving chambering student-case assignment problem
Ghazali, Saadiah; Abdul-Rahman, Syariza
2015-12-01
The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.
Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems
Cruz-Chávez, Marco Antonio
2015-11-01
This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.
Simulated annealing applied to two-dimensional low-beta reduced magnetohydrodynamics
The simulated annealing (SA) method is applied to two-dimensional (2D) low-beta reduced magnetohydrodynamics (R-MHD). We have successfully obtained stationary states of the system numerically by the SA method with Casimir invariants preserved. Since the 2D low-beta R-MHD has two fields, the relaxation process becomes complex compared to a single field system such as 2D Euler flow. The obtained stationary state can have fine structure. We have found that the fine structure appears because the relaxation processes are different between kinetic energy and magnetic energy
The performance of simulated annealing in parameter estimation for vapor-liquid equilibrium modeling
A. Bonilla-Petriciolet
2007-03-01
Full Text Available In this paper we report the application and evaluation of the simulated annealing (SA optimization method in parameter estimation for vapor-liquid equilibrium (VLE modeling. We tested this optimization method using the classical least squares and error-in-variable approaches. The reliability and efficiency of the data-fitting procedure are also considered using different values for algorithm parameters of the SA method. Our results indicate that this method, when properly implemented, is a robust procedure for nonlinear parameter estimation in thermodynamic models. However, in difficult problems it still can converge to local optimums of the objective function.
Optimización multiobjetivo en transmisiones de redes multicast utilizando Simulated Annealing
Yezid Donoso; Kadel Lacatt; Alfonso Jiménez
2005-01-01
En este artículo se presenta un método de optimización multiobjetivo para la solución del problema de balanceo de carga en redes de transmisión multicast, apoyándose en la aplicación de la meta-heurística de Simulated Annealing (Recocido Simulado). El método minimiza cuatro parámetros básicos para garantizar la calidad de servicio en transmisiones multicast: retardo origen destino, máxima utilización de enlaces, ancho de banda consumido y número de saltos. Los resultados devuel...
Comparing of the Deterministic Simulated Annealing Methods for Quadratic Assignment Problem
Mehmet Güray ÜNSAL
2013-08-01
Full Text Available In this study, Threshold accepting and Record to record travel methods belonging to Simulated Annealing that is meta-heuristic method by applying Quadratic Assignment Problem are statistically analyzed whether they have a significant difference with regard to the values of these two methods target functions and CPU time. Between the two algorithms, no significant differences are found in terms of CPU time and the values of these two methods target functions. Consequently, on the base of Quadratic Assignment Problem, the two algorithms are compared in the study have the same performance in respect to CPU time and the target functions values
Sousa, Tiago; Vale, Zita; Morais, Hugo
2013-01-01
The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs...... Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution...
Menin, O H; Martinez, A S; Costa, A M
2016-05-01
A generalized simulated annealing algorithm, combined with a suitable smoothing regularization function is used to solve the inverse problem of X-ray spectrum reconstruction from attenuation data. The approach is to set the initial acceptance and visitation temperatures and to standardize the terms of objective function to automate the algorithm to accommodate different spectra ranges. Experiments with both numerical and measured attenuation data are presented. Results show that the algorithm reconstructs spectra shapes accurately. It should be noted that in this algorithm, the regularization function was formulated to guarantee a smooth spectrum, thus, the presented technique does not apply to X-ray spectrum where characteristic radiation are present. PMID:26943902
Design of phase plates for shaping partially coherent beams by simulated annealing
Li Jian-Long; Lü Bai-Da
2008-01-01
Taking the Gaussian Schell-model beam as a typical example of partially coherent beams,this paper applies the simulated annealing (SA) algorithm to the design of phase plates for shaping partially coherent beams.A flow diagram is presented to illustrate the procedure of phase optimization by the SA algorithm.Numerical examples demonstrate the advantages of the SA algorithm in shaping partially coherent beams.An uniform flat-topped beam profile with maximum reconstruction error RE < 1.74% is achieved.A further extension of the approach is discussed.
Optimization of blade arrangement in a randomly mistuned cascade using simulated annealing
Thompson, Edward A.; Becus, Georges A.
1993-01-01
This paper presents preliminary results of an investigation on mistuning of bladed-disk assemblies aimed at capturing the benefits of mistuning on stability, while at the same time, minimizing the adverse effects on response by solving the following problem: given a set of N turbine blades, each being a small random perturbation of the same nominal blade, determine the best arrangement of the N blades in a mistuned cascade with regard to aeroelastic response. In the studies reported here, mistuning of the blades is restricted to small differences in torsional stiffness. The large combinatorial optimization problem of seeking the best arrangement by blade exchanges is solved using a simulated annealing algorithm.
Zhao Zhi-Jin; Zheng Shi-Lian; Xu Chun-Yun; Kong Xian-Zheng
2007-01-01
Hidden Markov models (HMMs) have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm (GA) and simulated annealing (SA) to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA's ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.
Extraction of Web Usage Profiles using Simulated Annealing Based Biclustering Approach
Rathipriya, R.; Thangavel, K.
2014-01-01
In this paper, the Simulated Annealing (SA) based biclustering approach is proposed in which SA is used as an optimization tool for biclustering of web usage data to identify the optimal user profile from the given web usage data. Extracted biclusters are consists of correlated users whose usage behaviors are similar across the subset of web pages of a web site where as these users are uncorrelated for remaining pages of a web site. These results are very useful in web personalization so that...
Mori, Takaharu; Okamoto, Yuko
2008-03-01
Gramicidin A is a hydrophobic 15-residue peptide with alternating D- and L-amino acids, and it forms various conformations depending on its environment. For example, gramicidin A adopts a random coil or helical conformations, such as &4.4circ;-helix, &6.3circ;-helix, and double-stranded helix in organic solvents. To investigate the structural and dynamical properties of gramicidin A in water and the hydrophobic environment, we performed molecular dynamics simulated annealing simulations with implicit solvent based on a generalized Born model. From the simulations, it was found that gramicidin A has a strong tendency to form a random-coil structure in water, while in the hydrophobic environment it becomes compact and can fold into right- and left-handed conformations of β-helix structures. We discuss the folding mechanism of the β-helix conformation of gramicidin A.
Chang Li; Coster, Daniel C.
2014-01-01
Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this paper, we present a modified, improved simulated annealing algorithm, providing practical approaches to specifications of the annealing cooling parameters, thresholds, and search neighborhoods for the perturbation scheme, which finds approximate D-optimal designs fo...
段谟意
2012-01-01
针对通信网络产生的拥塞问题,基于免疫克隆模拟退火算法提出了一种新的网络生存性评价方法(survivability algorithm based on immune clonal simulated annealing,SAICSA).该方法通过建立克隆变异和克隆交叉操作规则,并结合模拟退火接受准则来获得退火温度趋于零时的最优解.同时,以实际数据进行仿真实验,深入研究了网络生存性与失效边数、初始温度等影响因素之间的关系.实验结果表明,相比于免疫规划模拟退火算法和遗传模拟退火算法,SAICSA算法表现出较好的适应性.%In order to mitigate the network congestion by node failures, a novel survivability evaluation method (Survivability Algorithm based on Immune Clonal Simulated Annealing, SAICSA) is proposed by immune clonal simulated annealing algorithm. In this method, the clonal variation and clonal intersection regulations are presented at first, and the optimal solution is got by simulated annealing regulation when annealing temperature is tended to zero. Then, simulation was conducted to study the relationship between network survivability and failures node, as well as initial temperature with actual data. Compared SAIP (Simulated Annealing algorithm based on Immune Programming) and GSA (Genetic Simulated Annealing) algorithm, SAICSA algorithm has better adaptability.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system
Prediction of Flood Warning in Taiwan Using Nonlinear SVM with Simulated Annealing Algorithm
Lee, C.
2013-12-01
The issue of the floods is important in Taiwan. It is because the narrow and high topography of the island make lots of rivers steep in Taiwan. The tropical depression likes typhoon always causes rivers to flood. Prediction of river flow under the extreme rainfall circumstances is important for government to announce the warning of flood. Every time typhoon passed through Taiwan, there were always floods along some rivers. The warning is classified to three levels according to the warning water levels in Taiwan. The propose of this study is to predict the level of floods warning from the information of precipitation, rainfall duration and slope of riverbed. To classify the level of floods warning by the above-mentioned information and modeling the problems, a machine learning model, nonlinear Support vector machine (SVM), is formulated to classify the level of floods warning. In addition, simulated annealing (SA), a probabilistic heuristic algorithm, is used to determine the optimal parameter of the SVM model. A case study of flooding-trend rivers of different gradients in Taiwan is conducted. The contribution of this SVM model with simulated annealing is capable of making efficient announcement for flood warning and keeping the danger of flood from residents along the rivers.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif
2015-02-01
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com [Centre of Preparatory and General Studies, TATI University College, 24000 Kemaman, Terengganu, Malaysia and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Yusof, Fadhilah, E-mail: fadhilahy@utm.my [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Daud, Zalina Mohd, E-mail: zalina@ic.utm.my [UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia); Yusop, Zulkifli, E-mail: zulyusop@utm.my [Institute of Environmental and Water Resource Management (IPASA), Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Kasno, Mohammad Afif, E-mail: mafifkasno@gmail.com [Malaysia - Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia)
2015-02-03
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.
Temporary Workforce Planning with Firm Contracts: A Model and a Simulated Annealing Heuristic
Muhammad Al-Salamah
2011-01-01
Full Text Available The aim of this paper is to introduce a model for temporary staffing when temporary employment is managed by firm contracts and to propose a simulated annealing-based method to solve the model. Temporary employment is a policy frequently used to adjust the working hour capacity to fluctuating demand. Temporary workforce planning models have been unnecessarily simplified to account for only periodic hiring and laying off; a company can review its workforce requirement every period and make hire-fire decisions accordingly, usually with a layoff cost. We present a more realistic temporary workforce planning model that assumes a firm contract between the worker and the company, which can extend to several periods. The model assumes the traditional constraints, such as inventory balance constraints, worker availability, and labor hour mix. The costs are the inventory holding cost, training cost of the temporary workers, and the backorder cost. The mixed integer model developed for this case has been found to be difficult to solve even for small problem sizes; therefore, a simulated annealing algorithm is proposed to solve the mixed integer model. The performance of the SA algorithm is compared with the CPLEX solution.
Jiang, Chunhua; Yang, Guobin; Zhu, Peng; Nishioka, Michi; Yokoyama, Tatsuhiro; Zhou, Chen; Song, Huan; Lan, Ting; Zhao, Zhengyu; Zhang, Yuannong
2016-05-01
This paper presents a new method to reconstruct the vertical electron density profile based on vertical Total Electron Content (TEC) using the simulated annealing algorithm. The present technique used the Quasi-parabolic segments (QPS) to model the bottomside ionosphere. The initial parameters of the ionosphere model were determined from both International Reference Ionosphere (IRI) (Bilitza et al., 2014) and vertical TEC (vTEC). Then, the simulated annealing algorithm was used to search the best-fit parameters of the ionosphere model by comparing with the GPS-TEC. The performance and robust of this technique were verified by ionosonde data. The critical frequency (foF2) and peak height (hmF2) of the F2 layer obtained from ionograms recorded at different locations and on different days were compared with those calculated by the proposed method. The analysis of results shows that the present method is inspiring for obtaining foF2 from vTEC. However, the accuracy of hmF2 needs to be improved in the future work.
Design and optimization of solid rocket motor Finocyl grain using simulated annealing
Ali Kamran; LIANG Guo-zhu
2011-01-01
The research effort outlined the application of a computer aided design (CAD)-centric technique to the design and optimization of solid rocket motor Finocyl (fin in cylinder) grain using simulated annealing.The proper method for constructing the grain configuration model, ballistic performance and optimizer integration for analysis was presented. Finoeyl is a complex grain configuration, requiring thirteen variables to define the geometry. The large number of variables not only complicates the geometrical construction but also optimization process. CAD representation encapsulates all of the geometric entities pertinent to the grain design in a parametric way, allowing manipulation of grain entity (web), performing regression and automating geometrical data calculations. Robustness to avoid local minima and efficient capacity to explore design space makes simulated annealing an attractive choice as optimizer. It is demonstrated with a constrained optimization of Finocyl grain geometry for homogeneous, isotropic propellant, uniform regression, and a quasi-steady, bulk mode internal ballistics model that maximizes average thrust for required deviations from neutrality.
Using simulated annealing algorithms to solve the Schrödinger equation in muonic atoms
In many physical problems, the computation of exact wave functions for muons (particles about two hundred times heavier than electrons), bound in the extended Coulomb field created by the atomic nucleus, is required. Even though the problem is trivial under the assumption of point-like nuclear systems, the consideration of the nuclear finite-size necessitates the use of advantageous numerical techniques. In the case of non-relativistic bound muons, the solution of the Schrödinger equation is reliable, but for a relativistic description the solution of the Dirac equations for the bound muon is needed. In the present contribution, as a first step, we attempt to derive a method for solving the Schrödinger equation on the basis of simulated annealing algorithms. To this end, one may optimize appropriate parametric expressions for the wave function of a muon orbiting around complex nuclei by employing the simulated annealing method recently constructed to minimize multi parametric expressions in several physical applications
Simulating Astronomical Adaptive Optics Systems Using Yao
Rigaut, François; Van Dam, Marcos
2013-12-01
Adaptive Optics systems are at the heart of the coming Extremely Large Telescopes generation. Given the importance, complexity and required advances of these systems, being able to simulate them faithfully is key to their success, and thus to the success of the ELTs. The type of systems envisioned to be built for the ELTs cover most of the AO breeds, from NGS AO to multiple guide star Ground Layer, Laser Tomography and Multi-Conjugate AO systems, with typically a few thousand actuators. This represents a large step up from the current generation of AO systems, and accordingly a challenge for existing AO simulation packages. This is especially true as, in the past years, computer power has not been following Moore's law in its most common understanding; CPU clocks are hovering at about 3GHz. Although the use of super computers is a possible solution to run these simulations, being able to use smaller machines has obvious advantages: cost, access, environmental issues. By using optimised code in an already proven AO simulation platform, we were able to run complex ELT AO simulations on very modest machines, including laptops. The platform is YAO. In this paper, we describe YAO, its architecture, its capabilities, the ELT-specific challenges and optimisations, and finally its performance. As an example, execution speed ranges from 5 iterations per second for a 6 LGS 60x60 subapertures Shack-Hartmann Wavefront sensor Laser Tomography AO system (including full physical image formation and detector characteristics) up to over 30 iterations/s for a single NGS AO system.