Research on an Enhanced Genetic Algorithm with Cross Operator for Flexible Manufacturing Workshop
For the Flexible Job-shop Scheduling Problem(FJSP),this paper presents an improved adap-tive three-body crossover operator genetic algorithm model.The model aims to minimize the maximum completion time of the workpiece and effectively promotes the generation of the optimal solution by intro-ducing the three-body crossover operator.At the same time,combined with the adaptive crossover and mutation probability,the algorithm can improve the ability of searching the optimal solution and accelerate the population convergence.The experimental results show that the improved algorithm has better perfor-mance in flexible job-shop scheduling problems than traditional Gray Wolf optimization algorithm and hybrid quantum particle swarm optimization heuristic algorithm,and significantly improves the ability to search for optimal solutions.
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