This paper presents a combinatorial optimization procedure based on the simulated annealing approach for generation of optimal conΓΏguration of structural members. The work is based on altering the ΓΏnite element model of structure by removing or restoring elements to minimize the material use subject
Stochastic molecular optimization using generalized simulated annealing
β Scribed by Moret, M. A.; Pascutti, P. G.; Bisch, P. M.; Mundim, K. C.
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 583 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0192-8651
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β¦ Synopsis
We propose a stochastic optimization technique based on a Ε½ . generalized simulated annealing GSA method for mapping minima points of molecular conformational energy surfaces. The energy maps are obtained by Ε½ . coupling a classical molecular force field THOR package with a GSA procedure.
Ε½ . Unlike the usual molecular dynamics MD method, the method proposed in this study is force independent; that is, we obtain the optimized conformation without calculating the force, and only potential energy is involved. Therefore, we do not need to know the conformational energy gradient to arrive at equilibrium conformations. Its utility in molecular mechanics is illustrated by Ε½ . applying it to examples of simple molecules H O and H O and to 2 2 3 polypeptides. The results obtained for H O and H O using Tsallis 2 2 3
thermostatistics suggest that the GSA approach is faster than the other two Ε½ . conventional methods Boltzmann and Cauchy machines . The results for polypeptides show that pentalanine does not form a stable β£-helix structure, probably because the number of hydrogen bonds is insufficient to maintain the helical array. On the contrary, the icoalanine molecule forms an β£-helix structure. We obtain this structure simulating all β½, βΏ pairs using only a few steps, as compared with conventional methods.
π SIMILAR VOLUMES
Based on the simulated annealing technique and the constrained form of power system optimization problems, this paper develops a simulated-annealing-based optimization algorithm for power-system optimization problems. The algorithm is general, and it possesses the ability to determine the global opt