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RGV Optimization Problem Based on Genetic Algorithm

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DOI: 10.23977/meet.2019.93722

Author(s)

Cong Li

Corresponding Author

Cong Li

ABSTRACT

To analyze the working characteristics and adjustment strategies of RGV, and to consider the impact of its starting and stopping, waiting, recombination on the movement and transport capacity at the same time. Based on this foundation, the method of real time adjustment based on self-learning and modified inheritance calculation is proposed to discuss the code coding, selection, cross-fork variation and operation rule method of the method of adjustment, and the method of expert library self-learning of modified species group and proper co-solution is proposed. The high optimization calculation speed is verified through the simulation and process test, which proves that the moving force of ring shape is effective and high. This model and self-learning calculation method are feasible and effective.

KEYWORDS

Self-Learning, Modified Inheritance Calculation, High Optimization Calculation

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