Hybrid adaptive differential evolution for multi-objective flexible job shop scheduling problem

For multi-objective flexible job shop scheduling problem,this paper proposes a hybrid adaptive Differential evolution,which optimizes the three objective functions of minimizing the maximum processing time, minimizing the maximum machine load, and minimizing the total machine load. Combining the elite selection strategy using Pareto dominance relationship and simulated annealing algorithm, the algorithm performance is improved. Finally, simulation experiments were conducted to demonstrate the effectiveness of the proposed algorithm in solving multi-objective flexible job shop scheduling problems.