Replica creation strategy based on quantum evolutionary algorithm in data gird

Ma, Tinghuai; Yan, Qiaoqiao; Tian, Wei; Guan, Donghai; Lee, Sungyoung

doi:10.1016/j.knosys.2013.01.020

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…Eventually, generation after generation, the population must converge to the optimal solution we need. Essentially, this is an evolutionary strategy algorithm, a probabilistic algorithm that takes a random value and then calculates a comparative fitness [35]. The advantage of this algorithm is that the optimal concentration of ice slurry is a practical problem, and its mathematical model is necessarily very complicated, which is difficult to analyze by ordinary methods.…”

Section: Simulation Models/methodsmentioning

confidence: 99%

The Optimal Pumping Power under Different Ice Slurry Concentrations Using Evolutionary Strategy Algorithms

et al. 2021

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A suitable ice slurry fluid with a suitable ice concentration ratio can save operational costs. The design of the optimal ice slurry concentration focuses on finding an evolution strategy, which can further minimize the power consumption of the pump. A theoretical model was established to simulate the effect of different ice concentrations and flow rates on the performance of the pump. The data obtained were fitted by curve-fitting function. The process was modeled in the MATLAB evolutionary strategy algorithm to obtain the configuration scheme of the ice concentration and flow under different refrigeration capacities. The simulation results showed that when the required cooling capacity was 13.889 kWh, ice concentration was set to 19.68%, and flow rate was set to 2.1075 × 10−4 m3/s, the power consumption could be reduced by 23%.

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Section: Simulation Models/methodsmentioning

confidence: 99%

The Optimal Pumping Power under Different Ice Slurry Concentrations Using Evolutionary Strategy Algorithms

et al. 2021

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“…Tinghuai Ma, Qiaoqiao Yan and Wei Tia presented a based Quantum Evolutionary Algorithm (QEA) global replica creation strategy in data grid [9]. It divided optimization model into single and multi data replica creation two parts .It discussed three key technologies problems for each part.…”

Section: Related Workmentioning

confidence: 99%