Hybrid Discrete Differential Evolution Algorithm for Motor Train-Sets Scheduling
Chunmei Zhang, Haibin Yang, Jiajun Li · 2018
In order to solve the motor train-sets scheduling problem, a hybrid discrete differential evolution algorithm is proposed. The mathematical model is established for minimizing the total continuous time of one motor train-sets station. A hybrid algorithm of discrete differential evolution with scatter search is submitted to solve the motor train-sets scheduling problem. With regard to the initial population, more advanced designs derive from scatter search. Diversification generation method generates trial solutions. Improvement method transforms a trial solution into one or more enhanced trial solutions. In discrete differential evolution, new differential mutant and crossover operators are designed based on integer permutation. The performance of the proposed hybrid algorithm is tested on the model of the train-sets scheduling, which shows that it outperforms the compared algorithm. The optimal scheduling scheme can be obtained effectively to achieve the minimum total continuity time.