scholarly journals DNA sequence reconstruction based on innovated hybridization technique of probabilistic cellular automata and particle swarm optimization

2021 ◽  
Vol 547 ◽  
pp. 828-840 ◽  
Author(s):  
Wesam M. Elsayed ◽  
Mohammed Elmogy ◽  
B.S. El-Desouky
Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2333 ◽  
Author(s):  
Tawfiq M. Aljohani ◽  
Ahmed F. Ebrahim ◽  
Osama Mohammed

The optimal reactive power dispatch (ORPD) problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. This paper presents a new hybridization technique for solving the ORPD problem based on the integration of particle swarm optimization (PSO) with artificial physics optimization (APO). This hybridized algorithm is tested and verified on the IEEE 30, IEEE 57, and IEEE 118 bus test systems to solve both single and multiobjective ORPD problems, considering three main aspects. These aspects include active power loss minimization, voltage deviation minimization, and voltage stability improvement. The results prove that the algorithm is effective and displays great consistency and robustness in solving both the single and multiobjective functions while improving the convergence performance of the PSO. It also shows superiority when compared with results obtained from previously reported literature for solving the ORPD problem.


2020 ◽  
Vol 15 (12) ◽  
pp. 1450-1459
Author(s):  
Ying Niu ◽  
Hangyu Zhou ◽  
Shida Wang ◽  
Kai Zhao ◽  
Xiaoxiao Wang ◽  
...  

The DNA sequence design is a vital step in reducing undesirable biochemical reactions and incorrect computations in successful DNA computing. To this end, many studies had concentrated on how to design higher quality DNA sequences. However, DNA sequences involve some thermodynamic and conflicting conditions, which in turn reflect the evolutionary algorithm process implemented through chemical reactions. In the present study, we applied an improved multi-objective particle swarm optimization (IMOPSO) algorithm to DNA sequence design, in which a chaotic map is combined with this algorithm to avoid falling into local optima. The experimental simulation and statistical results showed that the DNA sequence design method based on IMOPSO has higher reliability than the existing sequence design methods such as traditional evolutionary algorithm, invasive weed algorithm, and specialized methods.


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