An Improved Genetic Algorithm for Solving the RGV Shop Scheduling Problem

Hao Fan, Xiaoyan Yu, De-qin Shu, Wei-hong Guan, Zhong-hao Guo, Shuo Feng
2019 Journal of Physics, Conference Series  
For the RGV (Rail Guide Vehicle) Shop Scheduling Problem, it is necessary to consider the RGV job scheduling under the condition of different processes with or without faults, and give the optimal solution. In this paper, the characteristics of the RGV job scheduling under the condition of different processes with or without faults are analysed and an improved genetic algorithm is proposed. The algorithm is improved in initial population selection, individual objective function, adaptive
more » ... n, selection and mutation operations and so on. The improved algorithm improves the convergence speed of the initial population to the optimal solution, enables the fitness function to select the optimal individual and avoids the problems of repeated solutions and local optimum solutions in cross-selection. The improved genetic algorithm and the traditional genetic algorithm are implemented. The experimental results show that under the condition of no fault and fault in the process, the maximum number of materials processed by the improved genetic algorithm is much higher than the traditional genetic algorithm. And the time efficiency of the improved algorithm is also better than the traditional genetic algorithm. The RGV Shop Scheduling Problem can be solved more effectively by the improved genetic algorithm.
doi:10.1088/1742-6596/1314/1/012133 fatcat:zboeapwpgzew3njqtsee5jecc4