Intensity modulated radiation therapy (IMRT) exhibits the ability to deliver the prescribed dose to the planning target volume (PTV), while minimizing the delivered dose to the organs at risk (OARs). Metaheuristic alg...
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ISBN:
(纸本)9781509055043
Intensity modulated radiation therapy (IMRT) exhibits the ability to deliver the prescribed dose to the planning target volume (PTV), while minimizing the delivered dose to the organs at risk (OARs). Metaheuristic algorithms, among them the simulating annealing algorithm (SAA), have been proposed in the past for optimization of IMRT. Despite the advantage of the SAA to be a global optimizer, IMRT optimization is an extensive computational task due to the large scale of the optimization variables. Therefore stochastic algorithms, such as the SAA, require significant computational resources. In an effort to elucidate the performance improvement of the SAA in highly dimensional optimization tasks, such as the IMRT optimization, we introduce for the first time to our best knowledge a parallel graphic processing unit (GPU)-based SAA developed in MATLAB platform and compliant with the computational environment for radiotherapy research (CERR) for IMRT treatment planning. Our strategy was firstly to identify the major "bottlenecks" of our code and secondly to parallelize those on the GPU accordingly. Performance tests were conducted on four different GPU cards in comparison to a serial version of the algorithm executed on a CPU. Our studies have shown a gradual increase of the speedup factor as a function of the number of beamlets for all four GPUs. Particularly, a maximum speedup factor of similar to 33 was achieved when the K40m card was utilized.
Intensity modulated radiation therapy (IMRT) exhibits the ability to deliver the prescribed dose to the planning target volume (PTV), while minimizing the delivered dose to the organs at risk (OARs). Metaheuristic alg...
详细信息
ISBN:
(纸本)9781509055050
Intensity modulated radiation therapy (IMRT) exhibits the ability to deliver the prescribed dose to the planning target volume (PTV), while minimizing the delivered dose to the organs at risk (OARs). Metaheuristic algorithms, among them the simulating annealing algorithm (SAA), have been proposed in the past for optimization of IMRT. Despite the advantage of the SAA to be a global optimizer, IMRT optimization is an extensive computational task due to the large scale of the optimization variables. Therefore stochastic algorithms, such as the SAA, require significant computational resources. In an effort to elucidate the performance improvement of the SAA in highly dimensional optimization tasks, such as the IMRT optimization, we introduce for the first time to our best knowledge a parallel graphic processing unit (GPU)-based SAA developed in MATLAB platform and compliant with the computational environment for radiotherapy research (CERR) for IMRT treatment planning. Our strategy was firstly to identify the major "bottlenecks" of our code and secondly to parallelize those on the GPU accordingly. Performance tests were conducted on four different GPU cards in comparison to a serial version of the algorithm executed on a CPU. Our studies have shown a gradual increase of the speedup factor as a function of the number of beamlets for all four GPUs. Particularly, a maximum speedup factor of ～33 was achieved when the K40m card was utilized.
simulating annealing algorithm was used in docking computation to predict a selected peptide VYMSPF(P2) binding site on the ectodomain of FGFR1. The peptide is located on the hydrophobic surface of the receptor, which...
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simulating annealing algorithm was used in docking computation to predict a selected peptide VYMSPF(P2) binding site on the ectodomain of FGFR1. The peptide is located on the hydrophobic surface of the receptor, which is critical for FGF binding. The synthesized peptide can effectively inhibit the mitogenic activity of aFGF, and has a potential to become a therapeutic agent as an aFGF antagonist.
A new approach for designing multiband rejection filters is proposed based on the optimization of a periodically phaseshifted long period fiber grating (LPG). The validity of the method is demonstrated by performing s...
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A new approach for designing multiband rejection filters is proposed based on the optimization of a periodically phaseshifted long period fiber grating (LPG). The validity of the method is demonstrated by performing simulations for the typical cases. It is shown that using the proposed synthesis method, spectral position, and bandwidth of the each reflection band can be controlled by varying the grating length and the phase shifting period. In addition, a desired number of rejection bands within the transmission spectrum can be generated using a phase-shifted LPG with an optimized phase shifting series. Furthermore, a number of unwanted rejection bands can easily be removed from the transmission spectrum by optimizing the phase shifting series.
The fault diagnosis of the pump-jack is as the background in the paper. A new negative selection algorithm is proposed combining the advantage of genetic algorithm and simulating annealing algorithm. The initial value...
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ISBN:
(纸本)9781424421138
The fault diagnosis of the pump-jack is as the background in the paper. A new negative selection algorithm is proposed combining the advantage of genetic algorithm and simulating annealing algorithm. The initial values of the detectors are initialized by genetic algorithm, thus the diversity of the detectors is retained, the scope of detecting is enlarged. The variable radius of detectors is introduced to cover non-self space efficiently. The redundancy of detectors is reduced and the efficiency is improved by using simulatingannealing. The method is used to diagnosis the faults of the pump-jack. The results are better. Especially the method can diagnosis unknown faults. It has great potentiality.
The fault diagnosis of the pump-jack is as the background in the paper. A new negative selection algorithm is proposed combining the advantage of genetic algorithm and simulating annealing algorithm. The initial value...
详细信息
The fault diagnosis of the pump-jack is as the background in the paper. A new negative selection algorithm is proposed combining the advantage of genetic algorithm and simulating annealing algorithm. The initial values of the detectors are initialized by genetic algorithm, thus the diversity of the detectors is retained, the scope of detecting is enlarged. The variable radius of detectors is introduced to cover non-self space efficiently. The redundancy of detectors is reduced and the efficiency is improved by using simulatingannealing. The method is used to diagnosis the faults of the pump-jack. The results are better. Especially the method can diagnosis unknown faults. It has great potentiality.
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