Motor Vehicle Maintenance Scheduling Model Based on Genetic algorithm

Motor Vehicle Maintenance Scheduling Model Based on Genetic algorithm

Yishuai Tian1*, Mingxuan Lou1, Xinhai Zhao1, Yalong Zheng1

1College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China.

international Journal of Natural Science1

To solve the problem of EMU maintenance planning time, we established a hybrid linear programming model based on adaptive genetic algorithm. According to the different levels of bullet train maintenance and the different arrival time, the constraint conditions are found, and the overall minimum maintenance time is taken as the objective function. Then the problem is transformed into a hybrid Flow-shop scheduling problem with unique process constraints, and an adaptive genetic algorithm is used to solve it again. It is concluded that the total maintenance takes 1125 minutes, and no blockage occurred in all EMU during the maintenance period. To provide a consistent basis for bullet train maintenance time and scheduling.

Keywords: Linear programming; Genetic algorithm; Hybrid; Flow-shop; Train maintenance

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How to cite this article:
Yishuai Tian, Mingxuan Lou, Xinhai Zhao, Yalong Zheng. Motor Vehicle Maintenance Scheduling Model Based on Genetic algorithm. International Journ-al of Natural Science and Reviews, 2020; 5:13. DOI: 10.28933/ijnsr-2020-05-1005


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