LAUSR

Abstract Aiming at the problem that the objective function design is not reasonable in the current flexible work shop scheduling, and the error of constraint solving process is large, the application of genetic algorithm in flexible work shop scheduling multi-objective optimization was proposed in this paper. Firstly, the mechanical work shop scheduling model was built. In the model, the objective function was based on the conditions of minimum total cost of work, the shortest time of workpiece circulation in the system and the minimum penalty for the completion of the work in advance, and the constraint conditions were composed of sequential constraints, resource constraints, cost constraints and other constraints. By using the priority matrix coding method, the chromosome was encoded and the initial solution was generated, the flexible work shop scheduling function was calculated, and the optimal scheduling solution of the objective function in the model was achieved. Experiments show that the algorithm can solve the problems in flexible work shop scheduling effectively, reduce production costs and resource consumption, and improve production efficiency and reliability.