Research on the scheduling strategy of intelligent manufacturing workshop based on machine learning

Abstract

In the context of industry 4.0, this paper proposes an improved genetic algorithm for optimizing the scheduling operation of smart manufacturing shops. Coding matrixes are separately developed for the manufacturing processes and machines and a retention operator is added to retain the optimal individuals in each generation of the population. After the approximate global optimal solution is obtained, the chromosomes are decoded by the adoption of an insertion greedy decoding algorithm. Simulation results have demonstrated the effectiveness of the algorithm.