Computational methods simulated annealing

XPLOR is a modern package of refinement programs that includes powerful procedures for energy refinement by simulated annealing, in addition to more traditional tools like least-squares methods and molecular-replacement searches. The package is available for use on many different computer systems. Simulated annealing for large molecules usually requires supercomputers. 

Natural computation denotes the following methods simulated annealing, simulated evolution strategy, genetic algorithms, artificial... 

Refinement of Conformations by Computational Methods 243 9.4.2.6 Simulated Annealing (SA)... 

Another interesting implementation of simulated annealing for continuous minimization (like a typical parameter estimation problem) utilizes a modification of the downhill simplex method. Press et al. (1992) provide a brief overview of simulated annealing techniques accompanied with listings of computer programs that cover all the above cases. 

The results from simulated annealing combined with an integration scheme demonstrates the feasibility of a vector field method. Once the proper vector field has been generated, several configurations of any desired density of linear chains can be generated with ease. While the computational efficiency of the minimization scheme is not sensitive to the number of modes, attention must be paid to the choice of the number of test points in the simulation box a large number of points requires lengthy calculations. 

There are methods that deliberately avoid the use of gradient and Hessian information. Such approaches typically require many more iterations but can nevertheless save overall on computation. Some popular ones are the Simplex Method, Genetic Algorithms, Simulated Annealing, Particle Swarm and Ant Colony Optimization, and variants thereof. 

Several methods have been developed to aid in the selection of descriptors to create a QSAR model. The use of brute computational force to test every possible combination of the above problem is wasteful. Methods such as the Stepwise Searches (45), Simulated Annealing (94), and Genetic Algorithms... 

The methods of simulated annealing (26), genetic algorithms (27), and taboo search (29) are three of the most popular stochastic optimization techniques, inspired by ideas from statistical mechanics, theory of evolutionary biology, and operations research, respectively. They are applicable to our current problem and have been used by researchers for computational library design. Because SA is employed in this chapter, a more-detailed description of the (generalized) SA is given below. 

An alternative to stochastic reconstruction of multiphase media is the reconstruction based on the direct simulation of processes by which the medium is physically formed, e.g., phase separation or agglomeration and sintering of particles to form a porous matrix. An advantage of this approach is that apart from generating a medium for the purpose of further computational experiments, the reconstruction procedure also yields information about the sequence of transformation steps and the processing conditions required in order to form the medium physically. It is thereby ensured that only physically realizable structures are generated, which is not necessarily the case when a stochastic reconstruction method such as simulated annealing is employed. 

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