基于深度强化学习种群优化的演化式分拣调度算法 .

The sorting operation of the production line in mechanical manufacturing has the double complexity of the problem and data. To optimize the sorting operation and improve production efficiency, this paper designed a method for data representation and an evolutionary algorithm based on population optimization. At the same time, this paper arranged and disclosed a real industrial data set. The method for data representation abstracted the original job data by referring to the bag-of-words model. The evolutionary algorithm used deep reinforcement learning to initialize the population in the genetic algorithm and introduced the elite retention strategy, which improved the optimization ability of the algorithm. Finally, it compared the proposed algorithm with other algorithms on the real industrial data set and travelling salesman problem data set. The results show that the proposed algorithm can find a better sorting sequence and the access path, which verifies the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]