Research on multi-objective flexible job scheduling based on improved genetic algorithm

Aiming at the problems of excessive machine load and idle machines caused by uneven production time distribution of processing machines in the workshop production process, a multi-objective flexible job shop scheduling model including balanced machine utilization was established, and an improved genetic algorithm was designed. Using POX crossover operator and multi-point crossover method, using neighborhood-based mutation operator. Finally, the experimental results verify that the algorithm is suitable for solving this kind of multi-objective flexible job shop scheduling problem, and the improved algorithm is also better than other comparison algorithms.